speech on modern technology

Speech about Modern Technology [1,2,3,5 Minutes]

Short 1 minute speech about modern technology.

Modern technology has made our life easier in many ways. It has made it possible to communicate with people across the world and share ideas with them. It has also offered us a lot of opportunities in the field of education, healthcare, and entertainment.

Modern technology is one of the most important inventions in human history. It has brought about so many changes in our lives and has allowed us to live longer healthier, and happier lives.

The incredible progress of modern technology has also made it possible for us to work from anywhere with a variety of tools at our disposal.

There are many ways that modern technology can improve your life. These include:

– A better collaboration with colleagues
– Improved productivity
– More efficient communication
– Access to new markets

Modern technology has brought a lot of benefits to our lives, such as the internet, mobile phones, and social media. The list of benefits is never-ending.

Some of the advantages are:

– More time for social interaction
– Increased productivity and efficiency
– Saving money on transportation costs

Quotes for Speech on Modern Technology

“Technology is just a tool. In terms of getting the kids working together and motivating them, the teacher is the most important.” – Bill Gates
“The advance of technology is based on making it fit in so that you don’t really even notice it, so it’s part of everyday life.” – Bill Gates
“The most important technology is the one that brings people together.” – Matt Mullenweg
“It has become appallingly obvious that our technology has exceeded our humanity.” – Albert Einstein
“The technology you use impresses no one. The experience you create with it is everything.” – Sean Gerety
“The great myth of our times is that technology is communication.” – Libby Larsen
“The human spirit must prevail over technology.” – Albert Einstein
“The real problem is not whether machines think but whether men do.” – B.F. Skinner
“Technology is anything that wasn’t around when you were born.” – Alan Kay
“We are stuck with technology when what we really want is just stuff that works.” – Douglas Adams
“The art challenges the technology, and the technology inspires the art.” – John Lasseter
“The advance of technology is based on making it fit in so that you don’t even notice it, so it’s part of everyday life.” – Bill Gates
“It’s supposed to be automatic, but actually, you have to push this button.” – John Brunner
“Technology is a useful servant but a dangerous master.” – Christian Lous Lange
“The technology itself is not transformative. It’s the school, the pedagogy, that is transformative.” – Tanya Byron

2 Minutes Speech about Modern Technology

Modern technology is a term that has been used to refer to the technologies developed during the 20th century. It has been used as a means of communication, transportation, entertainment and many more.

In the modern era, technology has become a necessity and an important part of our lives. We rely on it to make our lives easier and more convenient.

However, there are also some downsides to it. As technology advances, so do the threats that come along with it. In order to ensure that we are safe from these threats, we need to be aware of them and learn how they work.

Modern technology is not just a tool; it’s a necessity in today’s society.

We live in a world where there are so many technological advances that it’s hard to keep up with the pace of change.

There are so many advantages of Modern Technology that it is hard to list them all. One of the most significant advantages is that we can do more things at once and we can do them faster than ever before. Another advantage is that it helps us save time and money on a day-to-day basis.

3 Minutes Speech about Modern Technology

With the advancement of technology, the world has become more connected and more dependent on it.

Modern technology has made our lives easier but also more complicated. We are constantly bombarded with information from all around us and it is difficult to filter through what is important to us.

The importance of technology is not limited to the tech industry. Technology is a part of our daily life and it helps us in many ways.

Technology gives us an opportunity to do things faster and easier, which in turn makes our lives easier. It also helps us be more productive and efficient by providing us with new tools that make our work easier.

Modern technology is making the lives of people more convenient and better than ever before.

Modern technology has made our lives easier and more convenient. These advancements have also given us the opportunity to create new opportunities for ourselves.

The importance of technology in our lives is undeniable. It has made our lives so much easier and more convenient. It has also given us the opportunity to create new opportunities for ourselves.

Modern technology has been around for a while and it has made our lives easier. The list of advantages it provides is endless.

The list below are some of the advantages of Modern Technology:

– It helps us connect with people all over the world

– It helps us stay in touch with friends and family

– It helps us find information easily

– It helps us get work done more efficiently

5 Minutes Speech about Modern Technology

With the ever-changing technology, we are living in a world where everything is changing. The way we use our devices and the way we live our lives has changed significantly.

The increasing demand for content is something that has impacted modern technology in a big way. With so much content being generated every day, it’s hard to find people who have time to write all of it.

Modern technology has made it easier for people to generate content on their own and this has also led to a rise in people who are now self-publishing books and blogs.

Technology has always been an integral part of our lives. It has made our lives easier and better. However, it is also changing the way we live and work.

In this speech, I will explore how technology is changing the way we work and live – from how people communicate to how they eat or shop. We will also look at some of the most important technological innovations in recent years.

Technology has evolved in recent years with new technologies that are becoming more and more popular with time – such as virtual reality, augmented reality, artificial intelligence, machine learning, etc…

Modern technology has brought about a lot of changes in our lives. It has made life easier for us in many ways. However, it is important that we are aware of the dangers that this technology poses to us and the people around us.

There are many ways in which modern technology can be used to help humans. People can use it to improve their health, save time, and improve productivity.

Technology has been beneficial for society as a whole but there are also some disadvantages that come with it such as increased social inequality and environmental destruction.

Modern technology has brought us many benefits. They have improved our lives and are making our work easier and more efficient.

The list of advantages of Modern Technology is endless, but here are some examples:

– It allows us to store information in the cloud, which means that we can access it from any device at any time

– It helps to increase productivity by providing tools that help us work better and faster

– It provides access to knowledge through the internet

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Speech on Technology

Technology in This Generation

We are in a generation, where technology has surrounded us from all sides. Our everyday life runs on the use of technology, be it in the form of an alarm clock or a table lamp. Technology has been an important part of our daily lives. Therefore, it is important for the students to be familiar with the term technology. Therefore, we have provided a long speech on technology for students of all age groups. There is also a short speech and a 10 lines speech given in this article.

Long Speech on Technology

A warm welcome to everyone gathered here today. I am here to deliver a speech on technology which has taken a tremendous role in our day to day life. We all are in a generation where everything is dependent on technology. Let’s understand what technology is through the lens of Science.

Technology comes in the form of tangible and intangible properties by exerting physical and mental force to achieve something that adds value. For example, a mobile phone is tangible, and the network connection used by the phone is intangible. Technology has taken its place as indispensable, wherein it has resulted in economic benefits, better health care, time-saving, and better lifestyle.

Due to technology, we have a significant amount of knowledge to improve our lives and solve problems. We can get our work done efficiently and effectively. As long as you know how to access technology, it can be used and proves to benefit people of all ages greatly. Technology is constantly being modified and upgraded every passing year.

The evolution of technology has made it possible to achieve lots in less time. Technology has given tools and machines to be used to solve problems around the world. There has been a complete transformation in the way we do things because of contributions from scientific technology. We can achieve more tasks while saving our time and hence in a better place than our previous generation.

Right from the ringing of the morning alarm to switching off the fan, everything runs behind the technology. Even the microphone that I am using is an innovation of technology and thus the list continues. With several inventions of hi-tech products, our daily needs are available on a screen at our fingertips. These innovations and technologies have made our lives a lot easier. Everything can be done at the comfort of your home within a couple of hours or so. These technologies have not only helped us in the digital platform but have also given us innovations in the field of medical, educational, industrial as well as in agricultural sectors. If we go back to the older generations, it would take days to get any things solved, even if there were not many treatments for several diseases.

But today with the innovations of technology, many diseases can be treated and diagnosed within a shorter period of time. The relationship between humans and technology has continued for ages and has given rise to many innovations. It has made it easier for us to handle our daily chores starting from home, office, schools and kitchen needs. It has made available basic necessities and safer living spaces. We can sit at home comfortably and make transactions through the use of online banking. Online shopping, video calling, and attending video lectures on the phone have all been possible due to the invention of the internet.

People in the past would write letters to communicate with one another, and today due to technology, traditional letters have been replaced by emails and mobile phones. These features are the essential gifts of technology. Everything is just at our fingertips, right from turning on the lights to doing our laundry. The whole world runs on technology and hence, we are solely dependent on it. But everything has its pros and cons. While the benefits of technology are immense, it also comes with some negative effects and possibly irreversible damages to humanity and our planet.

We have become so dependent on technology that we often avoid doing things on our own. It as a result makes us lazy and physically inactive. This has also led to several health issues such as obesity and heart diseases. We prefer booking a cab online rather than walking a few kilometres. Technology has increased screen time, and thus, children are no longer used to playing in the playgrounds but are rather found spending hours on their phones playing video games. This has eroded children’s creativity, intelligence, and memory. No doubt, technology is a very essential part of our life, but we should not be totally dependent on it. We should practise being more fit and do regular activities on our own to maintain a healthy lifestyle.

The other aspects that have been badly affected us are that since technology replaced human interference, is unemployment. Social media platforms like Instagram, Facebook, Twitter, etc., were meant to connect people and increase our community circle. Still, it has made people all the more lonely, with cases of depression on the rise amongst the youth.

There are several controversies around the way world leaders have used technology in defence and industrialisation under the banner of development and advancements. The side effects of technology have resulted in pollution, climate change, forest fires, extreme storms, cyclones, impure air, global warming, land area getting reduced and natural resources getting extinct. It’s time we change our outlook towards selfish technology and bring about responsible technology. Every nation needs to set aside budgets to come up with sustainable technological developments.

As students, we should develop creative problem solving using critical thinking to bring clean technology into our world. As we improve our nation, we must think of our future for a greener and cleaner tomorrow. You would be glad to know that several initiatives have been initiated to bring awareness amongst children and youth to invent cleaner technology.

For example, 15-year-old Vinisha Umashankar invented a solar ironing cart and has been awarded the Earth Shot Prize by the Royal Foundation of the duke and duchess of Cambridge and honoured to speak at the COP26 climate change conference in Glasgow, Scotland. Her invention should be an inspiration to each one of us to pursue clean technology.

The top five technologically advanced countries are Japan, America, Germany, China and South Korea. We Indians will make our mark on this list someday. Technology has a vital role in our lives but lets us be mindful that we control technology and that technology doesn’t control us. Technology is a tool to elevate humanity and is not meant to be a self-destroying mechanism under the pretext of economic development. Lastly, I would like to conclude my speech by saying that technology is a boon for our society but we should use it in a productive way.

A Short Speech on Technology

A warm greeting to everyone present here. Today I am here to talk about technology and how it has gifted us with various innovations. Technology as we know it is the application of scientific ideas to develop a machine or a device for serving the needs of humans. We, human beings, are completely dependent on technology in our daily life. We have used technology in every aspect of our life starting from household needs, schools, offices, communication and entertainment. Our life has been more comfortable due to the use of technology. We are in a much better and comfortable position as compared to our older generation. This is possible because of various contributions and innovations made in the field of technology. Everything has been made easily accessible for us at our fingertips right from buying a thing online to making any banking transaction. It has also led to the invention of the internet which gave us access to search for any information on google. But there are also some disadvantages. Relying too much on technology has made us physically lazy and unhealthy due to the lack of any physical activity. Children have become more prone to video games and social media which have led to obesity and depression. Since they are no longer used to playing outside and socialising, they often feel isolated. Therefore, we must not totally be dependent on technology and should try using it in a productive way.

10 Lines Speech on Technology

Technology has taken an important place in our lives and is considered an asset for our daily needs.

The world around us is totally dependent on technology, thus, making our lives easier.

The innovation of phones, televisions and laptops has digitally served the purpose of entertainment today.

Technology has not only helped us digitally but has also led to various innovations in the field of medical science.

Earlier it took years to diagnose and treat any particular disease, but today with the help of technology it has led to the early diagnosis of several diseases.

We, in this generation, like to do things sitting at our own comfort within a short period of time. This thing has been made possible by technology.

All our daily activities such as banking, shopping, entertainment, learning and communication can be done on a digital platform just by a click on our phone screen.

Although all these gifts of technology are really making our lives faster and easier, it too has got several disadvantages.

Since we all are highly dependent on technology, it has reduced our daily physical activity. We no longer put effort to do anything on our own as everything is available at a minute's click.

Children nowadays are more addicted to online video games rather than playing outside in the playground. These habits make them more physically inactive.

FAQs on Speech on Technology

1. Which kind of technology is the most widely used nowadays?

Artificial Intelligence (AI) is the field of technology that is being used the most nowadays and is expected to grow even more even in the future. With AI being adopted in numerous sectors and industries and continuously more research being done on it, it will not be long before we see more forms of AI in our daily lives.

2. What is the biggest area of concern with using technology nowadays?

Protection of the data you have online is the biggest area of concern. With hacking and cyberattacks being so common, it is important for everyone to ensure they do not post sensitive data online and be cautious when sharing information with others.

Speech on Technology for Students and Children

3 minutes speech on technology.

We live in the 21st century, where we do all over work with the help of technology. We know technology as the name “technological know-how”. Read Speech on Technology.

Also, it implies the modern practical knowledge that we require to do things in an effective and efficient manner. Moreover, technological advancements have made life easier and convenient.

We use this technology on a daily basis to fulfill our interests and particular duties. From morning till evening we use this technology as it helps us numerous ways.

Also, it benefits all age groups, people, until and unless they know how to access the same. However, one must never forget that anything that comes to us has its share of pros and cons.

Benefits of Technology

In our day-to-day life technology is very useful and important. Furthermore, it has made communication much easier than ever before. The introduction of modified and advanced innovations of phones and its application has made connecting to people much easier.

Moreover, technology-not only transformed our professional world but also has changed the household life to a great extent. In addition, most of the technology that we today use is generally automatic in comparison to that our parents and grandparents had in their days.

Due to technology in the entertainment industry, they have more techniques to provide us with a more realistic real-time experience.

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Drawbacks of Technology

On the one hand, technology provides users with benefits or advantages, while on the other hand, it has some drawbacks too. These drawbacks or disadvantages negatively affect the importance of technology. One of the biggest problems, which everyone can easily observe, is unemployment.

In so many sectors, due to the over practice and much involvement of technology the machines have replaced human labor leading to unemployment.

Moreover, certain physiological researches teams have also proved their disadvantages. Because of the presence of social media applications like Facebook, Whatsapp, Twitter, Instagram, etc. the actual isolation has increased manifold. And ultimately it leads to increased loneliness and depression cases amongst the youngsters.

Due to the dependence of humans on technology, it has deteriorated the intelligence and creativity of children. Moreover, in today’s world technology is very important but if the people use it negatively, then there arises the negativity of the technology.

However, one thing that we need to keep in mind is that innovations are made to help us not to make us a victim of this technology.

How to use Technology?

Today we have technology that can transform lives. We have quick and vast access to the reservoir of knowledge through the Internet. So, we should make good use of it to solve the problems that we have around the world.

In the past, people use to write a letter to people that take many days to reach the destination, like the money order, personal letter, or a greeting card, but now we can send them much easily within few minutes.

Nowadays, we can easily transfer money online through our mobile phone and can send greetings through e-mail within a matter of minutes.

Besides, we cannot simply sum up the advantages and usefulness of technology at our fingertips.

In conclusion, I would say that it depends on a person that to what degree she/he wants to be dependent on technology. Moreover, there is nothing in the world that comes easy and it’s up to our conscience to decide what we want to learn from the things that we are provided to us.

Technology is not just a boom but a curse too. On one hand, it can save lives, on the other hand, it can destroy them too.

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Speech On Technology

Speech on Technology

Have you ever thought about the encroachment of technology in our lives? Can you imagine spending a day in your life without relying on technology? We live in a world where all major work is done with the assistance of technology. What are the benefits of technology, and what are its drawbacks? Read the article and develop a fine speech on technology.

Top 10 quotes to use in a speech on technology, speech on the benefits of technology, speech on the disadvantages of technology, short speech on technology, frequently asked questions on technology.

“Technology is best when it brings people together.” – Matt Mullenweg.
“It has become appallingly obvious that our technology has exceeded our humanity.” – Albert Einstein.
“It is only when they go wrong that machines remind you how powerful they are.” – Clive James.
“The Web as I envisaged it, we have not seen it yet. The future is still so much bigger than the past.”- Tim Berners-Lee.
“If it keeps up, man will atrophy all his limbs but the push-button finger.” – Frank Lloyd Wright.
“If future generations are to remember us more with gratitude than sorrow, we must achieve more than just the miracles of technology. We must also leave them a glimpse of the world as it was created, not just as it looked when we got through with it.” – Lyndon B. Johnson.
“Once a new technology rolls over you, if you’re not part of the steamroller, you’re part of the road.” – Stewart Brand.
“It’s not a faith in technology. It’s faith in people.” – Steve Jobs, Co-founder of Apple.
“Technology is a useful servant but a dangerous master.” – Christian Lous Lange.
“The advance of technology is based on making it fit in so that you don’t really even notice it, so it’s part of everyday life.”- Bill Gates.

Sample Speeches on Technology

A few samples of speeches on technology are given below. Go through them and utilise the resource for your better understanding of the topic.

Just like a coin, technology also has two sides, one is its benefits, and the other is its disadvantages.

There are multiple ways by which technology is favouring the lives of human beings. In the modern world, people are making maximum use of it. Technology became a great boon for us when it marked its advancement in the field of medical science. Through continuous evolution and updation, technology has reached a level that enables us to treat and cure many health disorders, including cancer and other chronic disorders. It has helped to save the lives of many humans, and truly it can be called a ‘life saver’.

The coming of the internet, mobile phones, and computers have eased the process of communication. With the support of all these advanced technologies, communication has become a simpler, faster, and more effective process. Can you imagine spending days waiting for a reply from your beloved ones? How strange will that be, right?

Another main advantage brought by technology is increased productivity. The overall production rate has increased drastically. With the assistance of huge machines and other technologies, the quantity of products has marked a rise without compromising on the quality. Technologies are evolving every single day; new discoveries are made frequently with the help of existing technologies and types of machinery. In one way or another, we can say that technologies aid new discoveries.

Technologies are making our lives easier. Imagine a situation where there is no internet and the world wide web. How will you receive information from all around the world? How long will it take to provide you with the exact information that you need? Will that be an updated one once it reaches you? Technologies are helping us to lead a secure life. Progressive changes that have happened in banking and money management are exceptional as well. Innovations like webcams and surveillance cameras have aided visual communication and security.

The benefits of technology is a very vast topic. Every single aspect of human life has the influence of technology in it. So pointing out each and every benefit of technology is impossible. Even though technology has many advantages, keep in mind that nothing can replace human intelligence. Always try to manage the use of technology, do not let it manage your lives.

We proudly proclaim that humans are the masters of technology; by doing that, we are actually trying to cover the ultimate truth behind it. We are completely dependent on technology. Even if the term advancement is often linked with technology, there exists multiple disadvantages too. With the encroachment of technology, people have lost their social life. It’s the supremacy of Artificial Intelligence (AI) over natural intelligence that is happening in the world right now. Humans are no longer social beings; they are just living beings with digital control.

Technological updates are happening in all sectors, and each and every new technological advancement offers us advantages and disadvantages. Let’s take a look at the disadvantages brought by digital technologies. Personal technologies like smartphones and laptops are isolating people from the larger physical community around them. More than getting engaged in public activities, what excites people more is their time on their personal gadgets.

Real lives and emotions are given very less value in the modern world. Even though technology is helping humans to save enough time, people are busy in their virtual realities. The world of social media is highly influencing the lives of people irrespective of age. People are getting dragged into that cyberspace. Let’s remember the words of Allison Burnett, “Only on Internet Technology can a person be lonely and popular at the same time.” How accurate these words are, right?

We always connect technology with something that is newly happening, right? But is that so? Technology is not a 21st century term. Technology is as old as civilisation. Every little change, even the use of primitive tools that were used for hunting in ancient times, can be connected with technology. Over the course of time, technology has undergone multiple changes, and such evolutions are clearly visible in all sectors of society. Do you know what the most precious thing on earth is? Is it the yacht History Supreme? Is it Antilla? Or is it ‘The Card Players’, a famous painting by French artist Paul Cezzane?

All these things may cost a lot, but not as much as time. Time is the most precious thing on earth, nothing can replace it, and it has to be valued. The assistance of modern technology has enabled us to save it. After the introduction of technologies, things that took hours and days for completion are now getting completed in seconds and minutes. Simultaneously, it is saving our money and bettering our lives, but never forget the words, “Too much of anything is good for nothing.”

Why is technology important?

There are multiple ways by which technology is favouring the lives of human beings. Technology became a great boon for us when it marked its advancement in the field of medical science. By continuous evolution and updation, technology has reached a level that enables us to treat and cure many health disorders, including cancer and other chronic disorders. It has helped to save the lives of many humans, and truly it can be called a ‘life saver’.

What are the top quotes to use in a speech on technology?

“Technology is best when it brings people together.” – Matt Mullenweg.
“It has become appallingly obvious that our technology has exceeded our humanity.” – Albert Einstein.
“It is only when they go wrong that machines remind you how powerful they are.” – Clive James.

How does technology affect our lives?

Even if the term advancement is linked with technology, there are multiple disadvantages. With the encroachment of technology, people have lost their social life. It’s the supremacy of Artificial Intelligence (AI) over natural intelligence that is happening in the world right now. Humans are no longer social beings; they are just living beings with digital control.

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Speech Writing /

Short Speech on Technology for School Students

Updated on
Nov 17, 2023

Have you ever noticed how fast everything around us has changed? Technology has become an integral part of our lives from modes of education to research and development. Can you imagine a day without relying on technology ? Do you want to make a call? Do you want to look for something on the internet ? Do you want to go on a trip? Guess what? None of this is possible if you don’t have access to technology. We’ll provide you with samples of short speech on technology, that you can use anywhere.

Table of Contents

1 1-minute Speech on Technology
2 Short Speech on Technology
3 10 Lines on Technology

‘ Technology is a useful servant but a dangerous master.’ – Christian Lous Lang

1-minute Speech on Technology

Also Read: Speech Writing Format, Samples and Examples

Short Speech on Technology

Also Read: 160+ Best and Easy English Speech Topics for Students

10 Lines on Technology

Here are 10 lines of technology that can be applied to any speech or writing topic. Feel free to use them.

Thanks to technology, we can accomplish things which seemed impossible a century ago.
From the wheel’s invention to the internet’s advent, technology has been a driving force behind human progress.
The rapid evolution of technology has led to unprecedented advancements in various fields, including medicine, education, and industry.
Smartphones, computers, and other devices have made information accessible at our fingertips, transforming the way we gather and share knowledge.
Automation and artificial intelligence have streamlined processes, increasing efficiency and productivity in many sectors.
The Internet of Things (IoT) connects everyday objects, enabling them to communicate and share data, creating a more interconnected world.
Social media platforms have facilitated global communication, breaking down geographical barriers and fostering a sense of community.
The development of renewable energy technologies is crucial for addressing environmental challenges and creating a sustainable future.
Cybersecurity has become a paramount concern as our reliance on technology increases, highlighting the importance of protecting digital assets and privacy.
As technology continues to advance, it presents both opportunities and challenges, requiring society to adapt and navigate this ever-changing landscape responsibly.

To write a short speech on technology, add small and informative details in your speech, such as the advancements in recent years, the advantages and disadvantages of technology, and how it can shape a better future. Make sure to keep it short, add stats and to the point to keep your audience engaged.

Here are 5 latest technological developments: Artificial intelligence (AI) and Machine Learning; 5g connectivity; Quantum computing; Virtual and Augmented reality; and Blockchain.

Technology refers to the development of scientific knowledge to develop tools, systems and processes.

For more information on such informative topics for your school, visit our speech writing website and follow Leverage Edu .

Shiva Tyagi

With an experience of over a year, I've developed a passion for writing blogs on wide range of topics. I am mostly inspired from topics related to social and environmental fields, where you come up with a positive outcome.

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Speech On Technology - 10 Lines, Short and Long Speech

Speech on Technology -

This generation has grown up with technology all around them. Whether it is an alarm clock or a table light, technology is a part of our daily lives. Our daily lives now include various kinds of technology which makes our life much easier than before. The students and the youngsters must understand what the term "technology" means.

10 Line Speech on Technology

Short speech on technology, long speech on technology.

Speech On Technology - 10 Lines, Short and Long Speech

Utilising scientific knowledge for practical uses is known as technology.

Technology has significantly altered how we live and the world works.

Things that were unthinkable a few years ago are now possible thanks to technology.

The use of scientific information and ideas for the benefit of humanity is referred to as technology.

Technology has become a part of our daily lives, from Simple Watches to Computers.

The most common form of communication is video conferencing, a gift from technology.

The word "technology" is derived from the ancient Greek words "techne" and "logos," where "techne" means "art, craft," and "logos" means "speed".

Technology is only sometimes a benefit, and it has frequently proven to be risky as well.

Both positive and harmful effects on humans are possible from creating nuclear weapons.

For the nation to advance and develop as it should, technology must be embraced.

Technology is the study and use of the technical properties of materials, science, and nature to develop mechanical, electrical, biological, and information systems that are more effective and facilitate daily life. Technology has existed since the Neolithic Age or before. The optimum use of pre-Neolithic people's abilities, resources, and established technology. Since then, technological advancements have dramatically improved people's lives.

Historical Era

The Industrial Revolution, which replaced manual labour with machine tools, marked the beginning of the first precise application of large-scale technology. Other scientists, engineers, and researchers worked to make technology more accessible to people. Our lives have become more dependent on technology because of this connection between humans and technology.

Technology has advanced from the atomic to the gross level of our daily lives. The idea of a world without technology is incomprehensible. Technology has made it feasible for us to see distant planets several light-years away. Our economy has been made more active by technology. People can get together with friends and family, whether they are nearby or not. The existence of technology in areas like commerce, automation, IT, healthcare, space exploration, education, and communication is apparent. As a result, technology has improved the efficiency and ease of human life.

Technology is the application of science to the production of goods. We are all drawn to new tools and methods as technology develops. Children start watching their parents and other family members use technology at a young age. They start to adjust in this way as well. Young children spend a lot of time playing video games, surfing the Internet, and avoiding reality. Technology use also promotes unemployment and deters pupils from learning. Dependence on technology also increases cybercrime and privacy issues, which opens the door for hackers.

The New Technological Era

Consumer electronics, computers, laptops, mobile phones, gadgets, and applications are among the technologies we use daily. Most importantly, it enhances human development and quality of life. Technology is obviously employed in many other disciplines, including science, medicine, agriculture, space exploration, education, and research.

Education and Technology

Children benefit from a better learning environment because of expanding educational technology. They can absorb and learn complex ideas. Children can share and discuss their questions with their teachers using technology. Additionally, they can connect with individuals globally to learn more and get resources for exams and project work.

Over time, technology has continued to advance the education sector. Technology makes a wide range of educational resources available to parents and students. Online collaboration between educators and classrooms all over the world is possible. On the Internet, students have immediate access to excellent knowledge. Teachers and students can use the many resources on the Internet for project work, research, and other purposes. The educational system has transformed due to online learning.

COVID-19 and Technology

Through the use of technology, the COVID-19 pandemic has caused a paradigm change. School-age children continue to receive their education at home, and schools are facilitating instructors' use of online learning from home. The student learned and used his 21st-century abilities through robots, augmented reality, and virtual classrooms. Each of these has significantly enhanced cooperation and communication.

Medicine and Technology

The quality of life and longevity of people as well as that of many medical professionals and students pursuing careers in medicine have all been enhanced by technological breakthroughs. The medical records of each patient are easily accessible. The doctor-patient relationship has undergone a significant transformation because of the Internet.

Everyone may keep up with the most recent medical advancements, share information on treatments, and assist one another in managing health difficulties. Thanks to contemporary technologies, you can now contact a doctor from the comfort of your home. Several websites and apps are available for getting doctors and obtaining medical assistance.

Examples | Examples of ground-breaking advancements in the healthcare sector include artificial organs, brain implants, networked sensors, and surgery. In addition to using several tools and software for administrative work, hospitals also employ digital marketing to advertise their services.

People are becoming increasingly dependent on various devices and technology, resulting in a lack of exercise and a sedentary lifestyle. The social isolation caused by smartphones and computers is growing. We acknowledge that technology is thriving in today's world and that this is advancing humanity. We are all dependent on technology and its uses. Everyone utilises technology to make things easier.

Explore Career Options (By Industry)

Construction
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Information Technology

Data Administrator

Database professionals use software to store and organise data such as financial information, and customer shipping records. Individuals who opt for a career as data administrators ensure that data is available for users and secured from unauthorised sales. DB administrators may work in various types of industries. It may involve computer systems design, service firms, insurance companies, banks and hospitals.

Bio Medical Engineer

The field of biomedical engineering opens up a universe of expert chances. An Individual in the biomedical engineering career path work in the field of engineering as well as medicine, in order to find out solutions to common problems of the two fields. The biomedical engineering job opportunities are to collaborate with doctors and researchers to develop medical systems, equipment, or devices that can solve clinical problems. Here we will be discussing jobs after biomedical engineering, how to get a job in biomedical engineering, biomedical engineering scope, and salary.

Ethical Hacker

A career as ethical hacker involves various challenges and provides lucrative opportunities in the digital era where every giant business and startup owns its cyberspace on the world wide web. Individuals in the ethical hacker career path try to find the vulnerabilities in the cyber system to get its authority. If he or she succeeds in it then he or she gets its illegal authority. Individuals in the ethical hacker career path then steal information or delete the file that could affect the business, functioning, or services of the organization.

GIS officer work on various GIS software to conduct a study and gather spatial and non-spatial information. GIS experts update the GIS data and maintain it. The databases include aerial or satellite imagery, latitudinal and longitudinal coordinates, and manually digitized images of maps. In a career as GIS expert, one is responsible for creating online and mobile maps.

Data Analyst

The invention of the database has given fresh breath to the people involved in the data analytics career path. Analysis refers to splitting up a whole into its individual components for individual analysis. Data analysis is a method through which raw data are processed and transformed into information that would be beneficial for user strategic thinking.

Data are collected and examined to respond to questions, evaluate hypotheses or contradict theories. It is a tool for analyzing, transforming, modeling, and arranging data with useful knowledge, to assist in decision-making and methods, encompassing various strategies, and is used in different fields of business, research, and social science.

Geothermal Engineer

Individuals who opt for a career as geothermal engineers are the professionals involved in the processing of geothermal energy. The responsibilities of geothermal engineers may vary depending on the workplace location. Those who work in fields design facilities to process and distribute geothermal energy. They oversee the functioning of machinery used in the field.

Database Architect

If you are intrigued by the programming world and are interested in developing communications networks then a career as database architect may be a good option for you. Data architect roles and responsibilities include building design models for data communication networks. Wide Area Networks (WANs), local area networks (LANs), and intranets are included in the database networks. It is expected that database architects will have in-depth knowledge of a company's business to develop a network to fulfil the requirements of the organisation. Stay tuned as we look at the larger picture and give you more information on what is db architecture, why you should pursue database architecture, what to expect from such a degree and what your job opportunities will be after graduation. Here, we will be discussing how to become a data architect. Students can visit NIT Trichy , IIT Kharagpur , JMI New Delhi .

Remote Sensing Technician

Individuals who opt for a career as a remote sensing technician possess unique personalities. Remote sensing analysts seem to be rational human beings, they are strong, independent, persistent, sincere, realistic and resourceful. Some of them are analytical as well, which means they are intelligent, introspective and inquisitive.

Remote sensing scientists use remote sensing technology to support scientists in fields such as community planning, flight planning or the management of natural resources. Analysing data collected from aircraft, satellites or ground-based platforms using statistical analysis software, image analysis software or Geographic Information Systems (GIS) is a significant part of their work. Do you want to learn how to become remote sensing technician? There's no need to be concerned; we've devised a simple remote sensing technician career path for you. Scroll through the pages and read.

Budget Analyst

Budget analysis, in a nutshell, entails thoroughly analyzing the details of a financial budget. The budget analysis aims to better understand and manage revenue. Budget analysts assist in the achievement of financial targets, the preservation of profitability, and the pursuit of long-term growth for a business. Budget analysts generally have a bachelor's degree in accounting, finance, economics, or a closely related field. Knowledge of Financial Management is of prime importance in this career.

Underwriter

An underwriter is a person who assesses and evaluates the risk of insurance in his or her field like mortgage, loan, health policy, investment, and so on and so forth. The underwriter career path does involve risks as analysing the risks means finding out if there is a way for the insurance underwriter jobs to recover the money from its clients. If the risk turns out to be too much for the company then in the future it is an underwriter who will be held accountable for it. Therefore, one must carry out his or her job with a lot of attention and diligence.

Finance Executive

Product manager.

A Product Manager is a professional responsible for product planning and marketing. He or she manages the product throughout the Product Life Cycle, gathering and prioritising the product. A product manager job description includes defining the product vision and working closely with team members of other departments to deliver winning products.

Operations Manager

Individuals in the operations manager jobs are responsible for ensuring the efficiency of each department to acquire its optimal goal. They plan the use of resources and distribution of materials. The operations manager's job description includes managing budgets, negotiating contracts, and performing administrative tasks.

Stock Analyst

Individuals who opt for a career as a stock analyst examine the company's investments makes decisions and keep track of financial securities. The nature of such investments will differ from one business to the next. Individuals in the stock analyst career use data mining to forecast a company's profits and revenues, advise clients on whether to buy or sell, participate in seminars, and discussing financial matters with executives and evaluate annual reports.

A Researcher is a professional who is responsible for collecting data and information by reviewing the literature and conducting experiments and surveys. He or she uses various methodological processes to provide accurate data and information that is utilised by academicians and other industry professionals. Here, we will discuss what is a researcher, the researcher's salary, types of researchers.

Welding Engineer

Welding Engineer Job Description: A Welding Engineer work involves managing welding projects and supervising welding teams. He or she is responsible for reviewing welding procedures, processes and documentation. A career as Welding Engineer involves conducting failure analyses and causes on welding issues.

Transportation Planner

A career as Transportation Planner requires technical application of science and technology in engineering, particularly the concepts, equipment and technologies involved in the production of products and services. In fields like land use, infrastructure review, ecological standards and street design, he or she considers issues of health, environment and performance. A Transportation Planner assigns resources for implementing and designing programmes. He or she is responsible for assessing needs, preparing plans and forecasts and compliance with regulations.

Environmental Engineer

Individuals who opt for a career as an environmental engineer are construction professionals who utilise the skills and knowledge of biology, soil science, chemistry and the concept of engineering to design and develop projects that serve as solutions to various environmental problems.

Safety Manager

A Safety Manager is a professional responsible for employee’s safety at work. He or she plans, implements and oversees the company’s employee safety. A Safety Manager ensures compliance and adherence to Occupational Health and Safety (OHS) guidelines.

Conservation Architect

A Conservation Architect is a professional responsible for conserving and restoring buildings or monuments having a historic value. He or she applies techniques to document and stabilise the object’s state without any further damage. A Conservation Architect restores the monuments and heritage buildings to bring them back to their original state.

Structural Engineer

A Structural Engineer designs buildings, bridges, and other related structures. He or she analyzes the structures and makes sure the structures are strong enough to be used by the people. A career as a Structural Engineer requires working in the construction process. It comes under the civil engineering discipline. A Structure Engineer creates structural models with the help of computer-aided design software.

Highway Engineer

Highway Engineer Job Description: A Highway Engineer is a civil engineer who specialises in planning and building thousands of miles of roads that support connectivity and allow transportation across the country. He or she ensures that traffic management schemes are effectively planned concerning economic sustainability and successful implementation.

Field Surveyor

Are you searching for a Field Surveyor Job Description? A Field Surveyor is a professional responsible for conducting field surveys for various places or geographical conditions. He or she collects the required data and information as per the instructions given by senior officials.

Orthotist and Prosthetist

Orthotists and Prosthetists are professionals who provide aid to patients with disabilities. They fix them to artificial limbs (prosthetics) and help them to regain stability. There are times when people lose their limbs in an accident. In some other occasions, they are born without a limb or orthopaedic impairment. Orthotists and prosthetists play a crucial role in their lives with fixing them to assistive devices and provide mobility.

Pathologist

A career in pathology in India is filled with several responsibilities as it is a medical branch and affects human lives. The demand for pathologists has been increasing over the past few years as people are getting more aware of different diseases. Not only that, but an increase in population and lifestyle changes have also contributed to the increase in a pathologist’s demand. The pathology careers provide an extremely huge number of opportunities and if you want to be a part of the medical field you can consider being a pathologist. If you want to know more about a career in pathology in India then continue reading this article.

Veterinary Doctor

Speech therapist, gynaecologist.

Gynaecology can be defined as the study of the female body. The job outlook for gynaecology is excellent since there is evergreen demand for one because of their responsibility of dealing with not only women’s health but also fertility and pregnancy issues. Although most women prefer to have a women obstetrician gynaecologist as their doctor, men also explore a career as a gynaecologist and there are ample amounts of male doctors in the field who are gynaecologists and aid women during delivery and childbirth.

Audiologist

The audiologist career involves audiology professionals who are responsible to treat hearing loss and proactively preventing the relevant damage. Individuals who opt for a career as an audiologist use various testing strategies with the aim to determine if someone has a normal sensitivity to sounds or not. After the identification of hearing loss, a hearing doctor is required to determine which sections of the hearing are affected, to what extent they are affected, and where the wound causing the hearing loss is found. As soon as the hearing loss is identified, the patients are provided with recommendations for interventions and rehabilitation such as hearing aids, cochlear implants, and appropriate medical referrals. While audiology is a branch of science that studies and researches hearing, balance, and related disorders.

An oncologist is a specialised doctor responsible for providing medical care to patients diagnosed with cancer. He or she uses several therapies to control the cancer and its effect on the human body such as chemotherapy, immunotherapy, radiation therapy and biopsy. An oncologist designs a treatment plan based on a pathology report after diagnosing the type of cancer and where it is spreading inside the body.

Are you searching for an ‘Anatomist job description’? An Anatomist is a research professional who applies the laws of biological science to determine the ability of bodies of various living organisms including animals and humans to regenerate the damaged or destroyed organs. If you want to know what does an anatomist do, then read the entire article, where we will answer all your questions.

For an individual who opts for a career as an actor, the primary responsibility is to completely speak to the character he or she is playing and to persuade the crowd that the character is genuine by connecting with them and bringing them into the story. This applies to significant roles and littler parts, as all roles join to make an effective creation. Here in this article, we will discuss how to become an actor in India, actor exams, actor salary in India, and actor jobs.

Individuals who opt for a career as acrobats create and direct original routines for themselves, in addition to developing interpretations of existing routines. The work of circus acrobats can be seen in a variety of performance settings, including circus, reality shows, sports events like the Olympics, movies and commercials. Individuals who opt for a career as acrobats must be prepared to face rejections and intermittent periods of work. The creativity of acrobats may extend to other aspects of the performance. For example, acrobats in the circus may work with gym trainers, celebrities or collaborate with other professionals to enhance such performance elements as costume and or maybe at the teaching end of the career.

Video Game Designer

Career as a video game designer is filled with excitement as well as responsibilities. A video game designer is someone who is involved in the process of creating a game from day one. He or she is responsible for fulfilling duties like designing the character of the game, the several levels involved, plot, art and similar other elements. Individuals who opt for a career as a video game designer may also write the codes for the game using different programming languages.

Depending on the video game designer job description and experience they may also have to lead a team and do the early testing of the game in order to suggest changes and find loopholes.

Radio Jockey

Radio Jockey is an exciting, promising career and a great challenge for music lovers. If you are really interested in a career as radio jockey, then it is very important for an RJ to have an automatic, fun, and friendly personality. If you want to get a job done in this field, a strong command of the language and a good voice are always good things. Apart from this, in order to be a good radio jockey, you will also listen to good radio jockeys so that you can understand their style and later make your own by practicing.

A career as radio jockey has a lot to offer to deserving candidates. If you want to know more about a career as radio jockey, and how to become a radio jockey then continue reading the article.

Choreographer

The word “choreography" actually comes from Greek words that mean “dance writing." Individuals who opt for a career as a choreographer create and direct original dances, in addition to developing interpretations of existing dances. A Choreographer dances and utilises his or her creativity in other aspects of dance performance. For example, he or she may work with the music director to select music or collaborate with other famous choreographers to enhance such performance elements as lighting, costume and set design.

Social Media Manager

A career as social media manager involves implementing the company’s or brand’s marketing plan across all social media channels. Social media managers help in building or improving a brand’s or a company’s website traffic, build brand awareness, create and implement marketing and brand strategy. Social media managers are key to important social communication as well.

Photographer

Photography is considered both a science and an art, an artistic means of expression in which the camera replaces the pen. In a career as a photographer, an individual is hired to capture the moments of public and private events, such as press conferences or weddings, or may also work inside a studio, where people go to get their picture clicked. Photography is divided into many streams each generating numerous career opportunities in photography. With the boom in advertising, media, and the fashion industry, photography has emerged as a lucrative and thrilling career option for many Indian youths.

An individual who is pursuing a career as a producer is responsible for managing the business aspects of production. They are involved in each aspect of production from its inception to deception. Famous movie producers review the script, recommend changes and visualise the story.

They are responsible for overseeing the finance involved in the project and distributing the film for broadcasting on various platforms. A career as a producer is quite fulfilling as well as exhaustive in terms of playing different roles in order for a production to be successful. Famous movie producers are responsible for hiring creative and technical personnel on contract basis.

Copy Writer

In a career as a copywriter, one has to consult with the client and understand the brief well. A career as a copywriter has a lot to offer to deserving candidates. Several new mediums of advertising are opening therefore making it a lucrative career choice. Students can pursue various copywriter courses such as Journalism , Advertising , Marketing Management . Here, we have discussed how to become a freelance copywriter, copywriter career path, how to become a copywriter in India, and copywriting career outlook.

In a career as a vlogger, one generally works for himself or herself. However, once an individual has gained viewership there are several brands and companies that approach them for paid collaboration. It is one of those fields where an individual can earn well while following his or her passion.

Ever since internet costs got reduced the viewership for these types of content has increased on a large scale. Therefore, a career as a vlogger has a lot to offer. If you want to know more about the Vlogger eligibility, roles and responsibilities then continue reading the article.

For publishing books, newspapers, magazines and digital material, editorial and commercial strategies are set by publishers. Individuals in publishing career paths make choices about the markets their businesses will reach and the type of content that their audience will be served. Individuals in book publisher careers collaborate with editorial staff, designers, authors, and freelance contributors who develop and manage the creation of content.

Careers in journalism are filled with excitement as well as responsibilities. One cannot afford to miss out on the details. As it is the small details that provide insights into a story. Depending on those insights a journalist goes about writing a news article. A journalism career can be stressful at times but if you are someone who is passionate about it then it is the right choice for you. If you want to know more about the media field and journalist career then continue reading this article.

Individuals in the editor career path is an unsung hero of the news industry who polishes the language of the news stories provided by stringers, reporters, copywriters and content writers and also news agencies. Individuals who opt for a career as an editor make it more persuasive, concise and clear for readers. In this article, we will discuss the details of the editor's career path such as how to become an editor in India, editor salary in India and editor skills and qualities.

Individuals who opt for a career as a reporter may often be at work on national holidays and festivities. He or she pitches various story ideas and covers news stories in risky situations. Students can pursue a BMC (Bachelor of Mass Communication) , B.M.M. (Bachelor of Mass Media) , or MAJMC (MA in Journalism and Mass Communication) to become a reporter. While we sit at home reporters travel to locations to collect information that carries a news value.

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Are you searching for a Corporate Executive job description? A Corporate Executive role comes with administrative duties. He or she provides support to the leadership of the organisation. A Corporate Executive fulfils the business purpose and ensures its financial stability. In this article, we are going to discuss how to become corporate executive.

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A multimedia specialist is a media professional who creates, audio, videos, graphic image files, computer animations for multimedia applications. He or she is responsible for planning, producing, and maintaining websites and applications.

Quality Controller

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A quality controller records detailed information about products with defects and sends it to the supervisor or plant manager to take necessary actions to improve the production process.

Production Manager

A QA Lead is in charge of the QA Team. The role of QA Lead comes with the responsibility of assessing services and products in order to determine that he or she meets the quality standards. He or she develops, implements and manages test plans.

Process Development Engineer

The Process Development Engineers design, implement, manufacture, mine, and other production systems using technical knowledge and expertise in the industry. They use computer modeling software to test technologies and machinery. An individual who is opting career as Process Development Engineer is responsible for developing cost-effective and efficient processes. They also monitor the production process and ensure it functions smoothly and efficiently.

AWS Solution Architect

An AWS Solution Architect is someone who specializes in developing and implementing cloud computing systems. He or she has a good understanding of the various aspects of cloud computing and can confidently deploy and manage their systems. He or she troubleshoots the issues and evaluates the risk from the third party.

Azure Administrator

An Azure Administrator is a professional responsible for implementing, monitoring, and maintaining Azure Solutions. He or she manages cloud infrastructure service instances and various cloud servers as well as sets up public and private cloud systems.

Computer Programmer

Careers in computer programming primarily refer to the systematic act of writing code and moreover include wider computer science areas. The word 'programmer' or 'coder' has entered into practice with the growing number of newly self-taught tech enthusiasts. Computer programming careers involve the use of designs created by software developers and engineers and transforming them into commands that can be implemented by computers. These commands result in regular usage of social media sites, word-processing applications and browsers.

Information Security Manager

Individuals in the information security manager career path involves in overseeing and controlling all aspects of computer security. The IT security manager job description includes planning and carrying out security measures to protect the business data and information from corruption, theft, unauthorised access, and deliberate attack

ITSM Manager

Automation test engineer.

An Automation Test Engineer job involves executing automated test scripts. He or she identifies the project’s problems and troubleshoots them. The role involves documenting the defect using management tools. He or she works with the application team in order to resolve any issues arising during the testing process.

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Technophrenia

On the interface between technology, people and society

How technology is changing language and the way we think about the world

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We are getting used to the idea of rapidly developing technologies changing what we can do and how we do things. What most people haven’t considered is how technologies affect our language and how these changes are affecting the way we speak and even the way we think.

One of the key ways we see this is when the name of a company becomes a way of doing something involving any product that is similar. Classic examples are “to hoover” which came from the early dominance of vaccuum cleaners from the Hoover Company .

Googling becomes a verb

More significantly is the use of the term “to google” which first came to prominence in 2002 when the American Dialect Society declared it word of the year. Later, in 2009, they declared “google” to be the the word of the decade.

Google had become a generic word meaning “to search the Internet” with any search engine, not just Google itself. But googling has become much more than just the mere act of typing words into a text box and clicking a button. We now understand the subtext when someone declares “I have googled you” or even that they have googled themselves. The idea that this act can now exert a powerful effect on the opinion we form of others has even resulted in laws formulated by the European Union giving individuals rights over search engine companies to have information about them removed in order to be “forgotten”.

Google has now become our collective global memory and googling is the process by which we access those memories. This, in turn, is simply a process that we have always engaged with called “ transactive memory ” in which we turn to people around us, usually people we know, to help us recall facts and memories. The invention of the Gutenberg press allowed us to outsource people to books. The difference now though is that Google is now always with us, has a vast database of information that it is getting increasingly better at letting you access, with the vaguest of questions. This in turn has had a dramatic effect on what we are able to achieve, not only as individuals, but as a society.

The act of computer programming for example has become much easier through the ability to learn new computer languages and solve problems by “googling” the answers. It could be argued that the boom in mobile phone apps would not have been possible without Ggoogle providing a mechanism to access the “transactive memories” of the thousands of knowledgeable programmers with the answers to any developer’s questions.

Interestingly, it has been [Google] themselves who have resisted , even at times through legal threats, the spread of “google” being used beyond its reference to the company. This is because if it does enter the language as a common term, Google could lose the protection of the name as a trademark. If Google becomes a common term, to mean any generic search, it could become a “generic trademark” like Cellophane, Aspirin, Escalator and others.

Industries become uberized

In a different example of a verb that has come from a proper noun but may have just as significant an impact on our social lives, we have “to uberize”. This comes from the company Uber whose business approach has disrupted an industry by using mobile apps backed with data analytics to provide cheaper taxi services to consumers. The concept of “uberization” has taken the general meaning of disrupting any industry through the use of technology to circumvent unnecessary bureaucracy and legislation. What is interesting about the use of the term uberization is that again, the subtext is not just about the actual process of transforming an industry into something more efficient or productive. Saying that an industry needs to be “uberized” is as much a commentary about its unwillingness to change, modernise and really meet consumers’ needs. This context is being built up with every new development in the ongoing battles and controversies that Uber is facing as it pushes through its disruption of the taxi industry.

Uber’s less successful contribution to our language has been the concept of “ surge pricing ”. The concept embodies basic economic principles to ensure that there are taxis willing to pick up consumers at the busiest times. It turns out that this is too hard for most consumers (and reporters) to understand and they have interpreted it simply as unfair price gouging.

As a new term, it is an interesting example however of how a term that was supposed to have a specific meaning has been turned into something completely different through popular usage.

How much has changed

There are many conversations that we could have today that would mean little to someone from 2005. Even though the definition of specific words could be given, it would need the entire context of how they have developed through the interplay of technology, individuals and society to have any real meaning. This is not the first time this has happened in history but certainly the increase in the pace of change has resulted in our language changing equally rapidly, and with it, our thoughts.

On a final historical note, you can wonder what George Bernard Shaw would have understood by the following statements? “My mother was hacked last night.” “What a great meal - I’ll upload it!” “If anyone’s out there, can you inbox me?’ "How many steps did you get today?” “Will you torrent me the next series?” “I’ve given up on windows.”

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Voice technology for the rest of the world

Project aims to build a dataset with 1,000 words in 1,000 different languages to bring voice technology to hundreds of millions of speakers around the world.

Voice-enabled technologies like Siri have gone from a novelty to a routine way to interact with technology in the past decade. In the coming years, our devices will only get chattier as the market for voice-enabled apps, technologies and services continues to expand.

But the growth of voice-enabled technology is not universal. For much of the world, technology remains frustratingly silent.

“Speech is a natural way for people to interact with devices, but we haven’t realized the full potential of that yet because so much of the world is shut out from these technologies,” said Mark Mazumder, a Ph.D. student at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and the Graduate School of Arts and Sciences.

The challenge is data. Voice assistants like Apple’s Siri or Amazon’s Alexa need thousands to millions of unique examples to recognize individual keywords like “light” or “off”. Building those enormous datasets is incredibly expensive and time-consuming, prohibiting all but the biggest companies from developing voice recognition interfaces.

Even companies like Apple and Google only train their models on a handful of languages, shutting out hundreds of millions of people from interacting with their devices via voice. Want to build a voice-enabled app for the nearly 50 million Hausa speakers across West Africa? Forget it. Neither Siri, Alexa nor Google Home currently support a single African language.

But Mazumder and a team of SEAS researchers, in collaboration with researchers from the University of Michigan, Intel, NVIDIA, Landing AI, Google, MLCommons and Coqui, are building a solution to bring voice technology to the rest of the world.

At the Neural Information Processing Systems conference last week, the team presented a diverse, multilingual speech dataset that spans languages spoken by over 5 billion people. Dubbed the Multilingual Spoken Words Corpus , the dataset has more than 340,000 keywords in 50 languages with upwards of 23.4 million audio examples so far.

“We have built a dataset automation pipeline that can automatically identify and extract keywords and synthesize them into a dataset,” said Vijay Janapa Reddi , Associate Professor of Electrical Engineering at SEAS and senior author of the study. “The Multilingual Spoken Words Corpus advances the research and development of voice-enabled applications for a broad global audience."

Voice interfaces can make technology more accessible for users with visual or physical impairments, or for lower literacy users. We hope free datasets like ours will help assistive technology developers to meet these needs.

Speech technology can empower billions of people across the planet, but there’s a real need for large, open, and diverse datasets to catalyze innovation.

This is just the beginning. Our goal is to build a dataset with 1,000 words in 1,000 different languages.

“Speech technology can empower billions of people across the planet, but there’s a real need for large, open, and diverse datasets to catalyze innovation,” said David Kanter, MLCommons co-founder and executive director and co-author of the study. “The Multilingual Spoken Words Corpus offers a tremendous breadth of languages. I’m excited for these datasets to improve everyday experiences like voice-enabled consumer devices and speech recognition.”

To build the dataset, the team used recordings from Mozilla Common Voice, a massive global project that collects donated voice recordings in a wide variety of spoken languages, including languages with a smaller population of speakers. Through the Common Voice website, volunteer speakers are given a sentence to read aloud in their chosen language. Another group of volunteers listens to the recorded sentences and verifies its accuracy.

The researchers applied a machine learning algorithm that can recognize and pull keywords from recorded sentences in Common Voice.

For example, one sentence prompt from Common Voice reads: “He played college football at Texas and Rice.”

First, the algorithm uses a common machine learning technique called forced alignment — specifically a tool called the Montreal Forced Aligner — to match the spoken words with text. Then the algorithm filters and extracts words with three or more characters (or two characters in Chinese). From the above sentence, the algorithm would pull “played” “college” “football” “Texas” “and” and “Rice.” To add the word to the dataset, the algorithm needs to find at least five examples of the word, which ensures all words have multiple pronunciation examples.

The algorithm also optimizes for gender balance and minimal speaker overlap between the samples used for training and evaluating keyword spotting models.

“Our goal was to create a large corpus of very common words,” said Mazumder, who is the first author of the study. “So, if you want to train a model for smart lights in Tamil, for example, you would probably use our dataset to pull the keywords “light”, “on”, “off” and “dim” and be able to find enough examples to train the model.”

“We want to build the voice equivalent of Google search for text and images,” said Reddi. “A dataset search engine that can go and find what you want, when you want it on the fly, rather than rely on static datasets that are costly and tedious to create.”

When the researchers compared the accuracy of models trained on their dataset against models trained on a Google dataset that was manually constructed by carefully sourcing individual and specific words, the team found only a small accuracy gap between the two.

For most of the 50 languages, the Multilingual Spoken Words Corpus is the first available keyword dataset that is free for commercial use. For several languages, such as Mongolian, Sakha, and Hakha Chin, it is the first keyword spotting dataset in the language.

“This is just the beginning,” said Reddi. “Our goal is to build a dataset with 1,000 words in 1,000 different languages.”

“Whether it’s on Common Voice or YouTube, Wikicommons, archive.org, or any other creative commons site, there is so much more data out there that we can scrape to build this dataset and expand the diversity of the languages for voice-based interfaces,” said Mazumder. “Voice interfaces can make technology more accessible for users with visual or physical impairments, or for lower literacy users. We hope free datasets like ours will help assistive technology developers to meet these needs.”

The corpus is available on MLCommons, a not-for-profit, open engineering consortium dedicated to improving machine learning for everyone. Reddi is Vice President and a board member of MLCommons .

The paper was co-authored by Sharad Chitlangia, Colby Banbury, Yiping Kang, Juan Manuel Ciro, Keith Achorn, Daniel Galvez, Mark Sabini, Peter Mattson, Greg Diamos, Pete Warden and Josh Meyer.

The research was sponsored in part by the Semiconductor Research Corporation (SRC) and Google.

Topics: AI / Machine Learning , Computer Science

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40 Speeches on Technology

These Speeches Highlight Some of the Top Gadgets in Honor of CES 2014

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Speech on Importance Of Technology

Imagine living in a world without technology. Hard to picture, isn’t it? Technology touches every part of your life, making it easier, faster, and more enjoyable.

Its importance cannot be overstated. From smartphones to space rovers, it shapes your today and builds your tomorrow. With technology, the impossible becomes possible.

1-minute Speech on Importance Of Technology

Ladies and Gentlemen,

Technology is like the magic wand of our times. It’s not just about shiny new phones or fast cars. It is a tool that is making our lives easier, better, and a lot more exciting.

Think about a day in your life. You wake up to the sound of an alarm, that’s technology. You step into a warm shower, thank technology for that. You call a friend living miles away, it’s all because of technology. It’s everywhere, touching every part of our lives.

Now, let’s talk about learning and knowledge. Thanks to technology, we can learn about anything, from anywhere, at any time. Imagine you are curious about the stars in the sky. With technology, you can explore the universe sitting right in your home. It is making education fun, engaging, and limitless.

What about health? Technology is helping doctors cure diseases that were once thought impossible to treat. It’s giving hope to the ill and making the world a healthier place.

And let’s not forget how technology is bringing us closer. Earlier, if a loved one lived far away, we could only write letters and wait for a reply. Now, with a single click, we can see and talk to them as if they are right in front of us. That’s the power of technology.

Sure, like everything, technology has its challenges. It’s up to us to use it wisely, for the good of all. Remember, technology is not just a tool, it’s a gift. It’s our guide to a brighter and better future.

Also check:

Essay on Importance Of Technology

2-minute Speech on Importance Of Technology

Ladies and gentlemen, boys and girls,

Let’s talk about technology today. Why is technology so important? It’s like asking why we need air to breathe. Technology is everywhere around us and it affects our lives in many ways.

Imagine waking up in the morning. What’s the first thing you do? Many of us check our phones. Our day starts with technology and ends with it. It’s not just about phones and computers. Even simple things like a toaster, a washing machine, or a lightbulb – all are examples of technology.

Now think about a world without technology. No phones, no computers, no cars, no electricity. We would have to walk miles to reach school or work. We couldn’t talk to our friends who live far away. We wouldn’t be able to learn new things from the internet. Life would be very hard, wouldn’t it?

This is why we need technology. It makes our lives easier. It saves us time. It helps us do things we couldn’t do before. It connects us with people all over the world. It helps us learn new things. It makes our world a smaller and better place.

But technology is not just about making life easier. It’s also about solving big problems. Think about doctors. They use technology to cure diseases, to heal the sick. Farmers use technology to grow more food. Scientists use technology to understand the world around us.

And what about the future? Technology will play an even bigger role. It will help us fight climate change. It will help us explore space. It will help us live longer and healthier lives. The possibilities are endless.

But it’s not enough just to use technology. We must also understand it. We must learn how to use it wisely. We must make sure it doesn’t harm us or our planet.

So, let’s embrace technology. Let’s learn about it. Let’s use it to make our lives better and to make the world a better place. Because without technology, we wouldn’t be where we are today. And with technology, who knows where we can go tomorrow?

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Informative Speeches on Technology

Speech Topics List for Extemporaneous Speaking

Technology's far-reaching impact touches just about everything in society, and informative speeches about technology can help audiences understand that influence. Speakers can rely on government research, data and studies as well as articles that appear in newspapers, magazines and in the broadcast media to inform their speech. Since informative speeches are meant to educate audiences, speakers should avoid persuasive or argumentative language.

Informative speeches about technology can focus on consumer issues such as trends and how-to demonstrations. Examining the trends of what people buy and how much they will spend can make great speech topics regarding just about any technological gadget. Speakers can inform audiences about the popular features people look for and how much they will pay for the latest technology to hit the market. Speakers may also choose to demonstrate a product they are familiar with; it gives speakers the opportunity to talk about how something works. Topics can also look at the history of technology and its evolution in certain sectors such as cell phones, personal listening devices, home computers and televisions.

Technology speeches about security can include topics about identity theft, virus protection and cyber security. Speeches about identity theft can inform audiences about how to avoid becoming a victim and how to check to see if someone stole their identity. Informative speeches can also cover virus protection software and types of Internet viruses. Cyber security topics can include the growth of experts needed in the field and its connection to homeland security and the corporate world. Speeches can also focus on educating people in cyber security, telling them where to get schooling in cyber security, possible careers and salary range.

Ethical topics in technology can focus on a number of areas where people use computers that raise ethical questions. Speeches can focus using photo manipulation software to alter photographs that change the way people appear including their face, body shape, the clothes they wear and even the setting of the actual photograph and portray it as an accurate representation of fact. Topics can also cover using the Internet to plagiarize research papers and information found in newspaper or magazine articles.

Giving a speech about technology and society can cover topics such as social media and lifestyle topics. Speeches about social media can include the types of social media websites available and how to use those websites to find old high school friends, long lost family members and even how to make the most of its existence for a business, community group or as a public relations tool. Topics about lifestyle can include how technology makes life easier, including looking for a job, shopping, researching information, personal banking and even playing games.

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Alex Barski began writing professionally in 2006. He is a former television news reporter now working in news management and has written for regional magazines and business journals in Pennsylvania. Barski has also served as a college professor, teaching courses in mass media and writing. He has a Bachelor of Arts in mass communications and English from King's College.

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Student Essays

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Speeches on Technology | [1, 2 & 3 Minute Speeches on Technology]

The modern technology is the most, essential and powerful tool of development. It is dual edged sword with both blessing, boon and bane, advantages and disadvantages, pros and cons for life.

List of Topics

The digital technology, science and internet has many impacts on life including impacts on jobs, social life, personal relationships, public speaking, laziness in lives etc.

Read here best selected speeches on Modern technology, its impacts, uses, pros and cons, blessing and bane etc for life in easy, persuasive, simple short, 1,2,3 minutes speeches on technology for students.

The Technology | Best Selected Speeches For Children & Students

The technology is the heart of human progress in the world of today. We have been witnessing the marvelous benefits of technology in our lives. It has become the part of parcel of our lives. In every walk of our life we are deeply influenced by the impacts of technology

1. Speech on Technology For Children & Students

Technology is the use of knowledge to create something to enhance life. All the equipment used in our daily lives are the byproduct of the technology. Simply we can say that technology is the scientific knowledge used to produce machinery and devices that can be used to provide different services and make our lives convenient and easy.

Now we are running through the post modern period, this age is called the age of science and technology. We are totally bound to live scientifically and we are bound to learn all about the science and technology. If we will not adopt scientific knowledge we won’t be able to lead life.

People these days have grown accustomed to the use of these technological inventions, we can not simply do without them. Technology is a boon to mankind. It has made our lives easy and convenient and has helped us exceedingly at every walk of life.

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It has paves the way of better living and gives way to new and innovative ideas. Technology certainly has given way to an improved lifestyle and contributed towards the growth of living standard and economies. The technology is the integral part of our life. It is ever evolving and is responsible for our changing lifestyle.

The Technology is not only a boon to us but it has many adverse impacts on our environment and on our lives. The excessive use of technological devices has given rise to various types of pollution.

The air pollution, soil pollution , Noise pollution and thermal and light pollution are mainly caused by advancement in technology and science. The Technology has also caused depletion of natural resources and many health issues growing with the increase in technology.

Technology has also caused unemployment because the work which was once done manually is being done with the help of machines. The excessive use of technology has also reduced physical activities. In the end I will point out that everything that we use in our daily life like gas stove, refrigerator, air conditioner, mobile phones, cars and all vehicles are all sourced by technology.

It has not only made life convenient for us but its negative repercussions can not be overlooked. Technology is destroying us physically and mentally.

2. Short Speech On Technology, Importance & Benefits for us

As we know that technology is commonly defined as the use of scientific and technical information to design and create machinery and electronic devices to facilitate and serve the mankind.

Nowadays the industrial technology has made the production process quicker and more efficient. The creative technology includes art, product design and advertising using software based devices.

There is excess use of architectural technology to design and build buildings. Indeed technology is a boon to us because it has made our life convenient and has benefited us to an unimaginable extent. Since last five decades we have entirely submitted ourselves to the use of technology. At every walk of life we use electronic devices to do our works easily. Not only at homes but at schools, colleges, universities and offices the technology is used.

All the tools that we use all are gifts of science and technology. Technology has not only benefited us but it has made us lazy and unproductive. Our physical and mental activities are reduced and we are entirely dependent of machines.

We have left to walk because we have got addictive to use motor bikes to go to different places. Instead of going by foot we use vehicles to go our working places. We have become machines and lost all natural instincts of a human because we are surrounded by machines.

Modern Technology Essays & Speeches for Students

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January 21, 2022 at 11:50 am

You know what, this is the best speech that I have ever learned and this is not only the one there are more of these in this website so thanks to whoever created this website

January 21, 2022 at 12:49 pm

Thanks for nice words

September 25, 2022 at 6:10 pm

Really nice speech . As i was searching for a speech but suddenly i got this speech which suites to be best for me . Nicely connected the things and more . Thank you the one who has written and thanks to the website developer (who provides the writer to express its words )

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Comput Intell Neurosci
v.2019; 2019

Speech Technology Progress Based on New Machine Learning Paradigm

Vlado delić.

1 University of Novi Sad, Faculty of Technical Sciences, 21000 Novi Sad, Serbia

Zoran Perić

2 University of Niš, Faculty of Electronic Engineering, 18000 Niš, Serbia

Milan Sečujski

Nikša jakovljević, jelena nikolić, dragiša mišković, nikola simić, siniša suzić, tijana delić.

Speech technologies have been developed for decades as a typical signal processing area, while the last decade has brought a huge progress based on new machine learning paradigms. Owing not only to their intrinsic complexity but also to their relation with cognitive sciences, speech technologies are now viewed as a prime example of interdisciplinary knowledge area. This review article on speech signal analysis and processing, corresponding machine learning algorithms, and applied computational intelligence aims to give an insight into several fields, covering speech production and auditory perception, cognitive aspects of speech communication and language understanding, both speech recognition and text-to-speech synthesis in more details, and consequently the main directions in development of spoken dialogue systems. Additionally, the article discusses the concepts and recent advances in speech signal compression, coding, and transmission, including cognitive speech coding. To conclude, the main intention of this article is to highlight recent achievements and challenges based on new machine learning paradigms that, over the last decade, had an immense impact in the field of speech signal processing.

1. Introduction

According to Kuhn's theory of scientific revolutions [ 1 ], the science makes progress through the revolutionary changes of prevailing scientific paradigms, where a paradigm represents a set of beliefs and values and technical and methodological procedures common to a scientific community. Paradigms define frames and models for solving scientific challenges. New solutions come with new generations who are ready to accept new truths and interdisciplinary approaches. New paradigms appear suddenly and provide new lights to a scientific problem, based on synergy of particular and specialized knowledge consolidated into a functional and coherent unity. Speech technology community investigates spoken language processing as an interdisciplinary research area ( Figure 1 ), [ 2 ]. After a short retrospective of the main scientific paradigms based on the knowledge of speech production and auditory perception, this article presents new achievements and perspectives based on the new machine learning paradigm related to neuroscience and advanced signal processing.

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Interdisciplinary nature of speech technologies, i.e., spoken language processing (adopted from [ 2 ]).

The roots of speech signal processing research were closely related to the needs of speech signal digitization. The pioneering solutions were deployed during the World War II due to a need of secure communication between the Allies. The system was named SIGSALY, and it utilized pulse-code modulation (PCM) to enable the first transmission of voice using digital equipment [ 3 ]. In the next decades, the focus of researchers was on standardizing rules of digital telephony in order to provide high quality of reconstructed speech signal in the wide range of speech signal variances [ 4 – 7 ]. The compression paradigms regarding these systems have not changed significantly for decades. Particularly, the focus of research has slightly been moved toward improving the signal quality at the receiving end or toward reducing the required bit rate [ 8 – 13 ]. However, the significant development of computer technology in the last decade has enabled research into new approaches to advanced speech signal processing including adaptive machine learning methods [ 14 ]. Recent trends include cognitive speech coding so that there is a paradigm shift from perceptual (auditory) toward cognitive (auditory plus cortical) speech signal processing [ 15 ].

Modern speech technology systems rely on interdisciplinary research in the areas of multimodal signal processing and artificial intelligence, and a number of methods and algorithms have been developed with the aim of solving various problems: dialogue systems based on speech recognition and synthesis, including emotional speech, speaker identification and verification, as well as speech signal coding and transmission, denoising and detection of signals in the presence of noise, quality enhancement, and medical diagnostics based on the analysis of human voice. Recent progress in most of these speech technology topics will be discussed in more details in the following sections.

Spoken language processing (SLP) is an interdisciplinary research area that has attributes of computational intelligence. SLP lies in the intersection of linguistics, psychology, engineering, and artificial intelligence (AI) [ 2 ]. Advanced signal processing and machine learning methods are positioned in the adopted view to the interdisciplinary character of SLP, and both interconnections and intersections of different disciplines are shown and presented in a novel point of view ( Figure 1 ). Instead of using the original term “pattern processing” in Figure 1 , we have opted for the more common term “signal processing and machine learning (SP&ML),” which represents the overlap between the community of engineering and AI disciplines. With linguistic aspects included, they compose the natural language processing (NLP) field. Human-computer interaction (HCI) draws experience and methodology from the fields of engineering and psychology, and with the knowledge from linguistics included, they form a basis for the study and development of dialogue systems.

The interconnection of psycholinguistics and AI is the foundation of cognitive science or neurolinguistics. Neurolinguistics has been treated here as the neuroscience of speech. Neurolinguistics is presented in Figure 1 as dominantly linguistics discipline but connected to AI through computer linguistics which is on the intersection between AI and linguistics from one side and also connected to psychology through psycholinguistics, which is on the intersection between psychology and linguistics from other side. Neurolinguistics is on the opposite side from the engineering point of view. The neuroscience of speech can also be considered as an area of cognitive science, and cognition is inherent part of both speech perception (in the phase of understanding, the meaning of the message conveyed by spoken language) and speech production (in the phase of composing, a message intended to convey a certain meaning). Finally, SLP combines knowledge from the interdisciplinary areas of SP&ML, HCI, psycholinguistics, and computer linguistics, or more precisely NLP, cognitive sciences, dialogue systems, and information access.

Speech technologies are based on speech signal processing that spans a wide range of topics, while the focus in this review article is on three areas where the authors have the most expertise:

Fundamental topics (speech analysis and synthesis, sound waves and speech features, speech production, auditory perception, and cognition including the linguistic aspect)
Dialogue systems based on speech recognition and text-to-speech synthesis (emotional speech recognition and text-to-speech synthesis including voice and style conversion)
Speech coding, compression, and transmission

Speech technology fields within the scope of the paper are presented in Figure 2 as a unified framework that encompasses covered topics, showing their complementarity, ranges and borders, interconnections, and intersections in the interdisciplinary area of SLP.

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Unified framework that encompasses speech signal processing fields in the scope of the article.

A brief retrospective and some perspectives of the speech technology fields shown in Figure 2 are presented in the following sections. Fundamental topics are shown in the middle of Figure 2 and presented in Section 2 , covering speech production and perception analysis, including cognitive and linguistic point of views. More details related to the progress in speech recognition and speech synthesis, as well as their contributions to a new generation of human-machine speech dialogue systems, are presented in Section 3 . Finally, the progress in speech signal compression, coding, and transmission is presented in Section 4 , including contributions of the authors to the area. Most of these advancements are based on the new deep learning paradigm and our better understanding of neuroscience and modelling of cognitive aspects of spoken language communication.

2. Progress in Speech Analysis and Knowledge of Spoken Language Nature

Knowledge related to the nature of spoken language is essential for efficient coding and transmission as well as satisfactory real-time human-machine speech interaction. Speech models based on either speech production or auditory perception were inherent parts of most successful algorithms. Most recent neuro-inspired computational models are based on knowledge of cognitive speech processing models [ 16 ]. After a brief review of sound pressure waves and speech signal features, speech production and auditory perception including cognitive and linguistic points of view will be elaborated in more detail in the following subsections.

2.1. Sound Pressure Waves and Speech Signal Features

Sound propagates as a continuum of acoustic waves (sound pressure), and, once received, it can be recorded, digitized, coded, transmitted, processed, and reproduced. In case of speech sounds, frequencies relevant for recognizing what was said and who has said it are located mostly below 4 kHz and hardly ever above 7-8 kHz, which is just a portion of the entire frequency range of the human auditory sense [ 17 ]. This fact was the basis of the design of analogue telephone communication systems, including the choice of microphones used. For that reason, a speech signal is sampled at 8 kHz (for a basic level of quality) or 16 kHz (if a higher level of quality is desired). It is also well known that the dynamic range from the softest to the loudest sounds in average human speech is approximately 40 dB. Even if whisper and elevated voice are included, this dynamic range is rarely above 50 dB [ 14 ]. For these reasons, the requirements for a microphone needed to record voice are typically less strict than in case of recording, e.g., music. As to quantization, it is known that each bit contributes to the signal-to-noise ratio (SNR) by 6 dB, which means that the quantization noise is practically inaudible if 8 bits are used for coding every sound sample [ 4 ]. Thus, the typical case of using the sampling rate of 8 kHz and 8 bits per sample produces the bit rate of 64 kbits/s. A lot of effort has been invested to reduce this rate without significant loss of quality at the receiving side, and Section 4 is devoted to this subject.

Digitalization including quantization is the basis of all digital speech processing techniques. If the aim is to represent speech compactly and robustly, as is the case in automatic speech recognition or most types of speech coding for transmission, one of the basic questions is the selection of relevant features that will enable fast, accurate, and robust recognition of speech (or the speaker, language, or even emotion), and/or fast and efficient speech coding for transmission without significant loss of quality. Linear predictive coding (LPC) and LPC analysis have fundamental significance in speech signal modelling and speech feature estimation [ 18 ]. Many speech coding schemes are based on LPC including Low Delay-Code Excited Linear Prediction (LD-CELP) coding scheme defined by G.728 standard, Conjugate Structure Algebraic Code-Excited Linear Prediction (CS-ACELP) coding scheme defined by G.729A standard, Algebraic Code-Excited Linear Prediction coding scheme defined by G.723.1 standard, and Adaptive Multi-Rate Wide-Band (AMR-WB) coding scheme defined by G.722.2, standards which are used in today mobile voice communication and VoIP [ 5 , 7 ].

One of speech production models is also based on LPC analysis and provides speech feature sets describing speech spectrum, which is most important for speech recognition [ 19 ]. The main scope of speech signal and data processing in real time (or limited time) is to reduce the amount of data (speech features), while providing high quality of representation of such a reduced signal, that is, data source. The realization of this goal is supported by statistical signal and data processing as well as methods and algorithms which deal with signal and data reduction [ 20 ]. The most efficient methods and algorithms incorporate adaptation, and these topics will be elaborated in more details in the next sections.

2.2. Speech Production and Auditory Perception

Figure 3 shows a block diagram of both speech production and perception. Text-to-speech synthesis (TTS) and automatic speech recognition (ASR) are shown in parallel as corresponding processes performed by machines. Speech and language are learned, while the sense of hearing is innate. There are a lot of differences among human and machine speech production and perception, but the increase in the ability of machine learning paradigms to simulate human speech production mechanism, as well as auditory perception and cognition abilities, will inevitably bring about an increase in the accuracy of ASR and naturalness of TTS.

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Block diagram of speech production and speech perception and corresponding processes performed by machines carrying out text-to-speech synthesis (TTS) and automatic speech recognition (ASR).

Speech communication between humans begins and ends at the cognitive level of message composition and interpretation. Taking into account the average speech rate of 10–12 phones per seconds and the number of phones in a language, which typically corresponds to 5 or 6 bits needed to encode them, a speech message conveyed as text could be considered to correspond to a bit rate of 50–60 bits per second. The speaker plans not only what to say but also how to say it—(s)he controls the volume, speech rate, and intonation (prosody)—any of which can carry linguistic, and also paralinguistic and extralinguistic information [ 21 ]. With that information added, the bit rate can be considered to increase to several hundreds of bits per second.

Once the speaker decides what to say and how to say it, an appropriate sound wave is produced through nervous and muscular activity [ 22 , 23 ]. In that, phones are not pronounced in isolation, but the articulatory targets required for corresponding phonemes are rarely reached, leading to the coarticulation effect, which aggravates the task of ASR. Most often, the entire speech apparatus is considered through the source-filter model, where the activity of vocal folds defines the excitation and the remainder of vocal tract acts as a filter and shapes the sound spectrum [ 19 , 21 ]. Besides being dependent on the phone, the acoustic features of the speech signal at a particular moment also carry information relevant to the speaker and thus represent a biometrical feature which can reveal the speaker's identity [ 24 ] and possibly other factors related to the speaker or to the message. Including the influence of speaker variability, the bit rate at this level increases to several thousand bits per second. This segment of speech communication is studied by articulatory and acoustical phonetics, and its machine counterpart is TTS, namely, the module charged with the production of the artificial speech signal itself.

Distribution of speech sample amplitudes is nonuniform, and this knowledge is used in nonuniform speech signal coding defined by µ -law and A-law [ 25 ], while some new research results provide better solutions based on adaptive algorithms. The speech production mechanism articulates a series of phonemes nonuniformly, according to an empirical statistical law formulated by George Kingsley Zipf, a linguist [ 26 ], referring to the principle of the least effort from evolutionary biology field: interlocutors try to understand each other using phonemes and words that are easier for production and perception in a particular context. The knowledge of phoneme and word statistics has been introduced into ASR algorithms long ago, and stochastic speech models like Hidden Markov model (HMM) [ 27 ] were the prevailing scientific paradigm and represented the state of the art in speech recognition and synthesis community for decades.

On the other side, the continuum of acoustic waves reaches the ear of the listener and certain frequencies excite the eardrum, and over the malleus, incus, and stapes, they excite the cochlea, where spectral analysis is performed, based on the movement of the basilar membrane, whose length is about 35 mm [ 17 , 22 , 23 , 25 , 28 ]. The hair cells in the cochlea respond to different sounds based on their frequency so that high-pitched sounds stimulate the hair cells in the lower part of the cochlea, while low-pitched sounds stimulate the upper part of the cochlea [ 28 ]. Thus formed neural impulses are sent to the central auditory system in the brain [ 22 ], and based on spectral differences, the brain recognizes relevant acoustic differences and attempts to recover the string of phones that the original message was composed of, taking into account its language model (at the level of morphology, syntax, semantics, and pragmatics). It can thus be considered that the task of ASR is to reduce the bit rate of, e.g., 64 kbits/s (digitized speech) to a bit rate of 50–60 bits/s (plain text), which would correspond to the textual contents of the message without speech prosody.

However, speech perception, which principally relies on the sense of hearing, is a nonlinear process. As is the case with other human senses (vision, taste, touch, and smell), auditory perception of both sound pressure level (SPL) and fundamental frequency (f0, pitch) follows the Weber–Fechner law [ 28 ] from psychophysics: a change perceived as linear corresponds to an exponential change in the physical stimulus. Apart from SPL and pitch, perception of sound is affected by the distribution of sound energy across frequencies, i.e., the spectrum of the sound, which usually represents a mixture of a sequence of discrete frequency components (timbre), as in the case of periodic sounds, and a continuous mix of nonharmonic or random frequency components, as in the case of various types of noise [ 22 , 28 ]. This is why common speech features like cepstral coefficients are considered to be located at frequencies rescaled from Hz to mel-scale–MFCC; they are estimated by cepstral analysis from speech frames of 20–30 ms together with their first and second derivatives calculated from several successive frames [ 29 ].

Auditory scene analysis is the process by which the auditory system separates individual sounds in natural-world situations [ 30 , 31 ]. Regardless of whether sound is received by a human ear or a microphone, the incident sound pressure wave represents a sum of pressure waves coming from different individual sources, which can be either human voices or any other sound sources. These sounds usually overlap in both time and frequency. Nevertheless, the human auditory system is usually able to concentrate on an individual sound source at a time [ 23 , 31 ]. While listening and separating one source, the listener constructs a separate mental description for that source. Although he/she cannot actively listen to two sound sources simultaneously, he/she can switch immediately his/her attention from one to the other [ 30 ]. For example, if a student listens to the teacher, he ignores the noise from LCD projector and a colleague who may be speaking to him; if he switches the focus to his colleague, he cannot actively listen to the teacher anymore. Furthermore, if a human listener follows the context, he/she is able to reconstruct some phonemes or entire words that he/she may not be able to hear for some reason. Humans are as successful in sound separation as they are more experienced in real-word situations and they always analyse the incoming signal using heuristic processes. As the ultimate step of the hearing process, human auditory cortex constructs a cognitive representation of the received sound wave. Without the cognition step, sound waves coming to the ears are not perceived. Heuristic analysis is based on (ir)regularities in the sum of underlying sounds.

Individual sounds differentiate from each other in at least one of the following dimensions: time, space, and frequency spectrum [ 28 , 31 ]. Temporal and spatial sensations in the human auditory system are presented in more details in [ 32 ]. In the time dimension, two sounds can have some onset/offset asynchrony. In a specific environment, binaural hearing enables the localization of sound sources, which is easier, but also often more important, in the horizontal plane where human ears are positioned than in the vertical plane. The spectrum of frequency components can determine the perceived pitch, timbre, loudness, and the difference in the spectra of sounds received by both ears enables the localization of sound sources [ 23 , 31 , 32 ]. Pitch is related to the fundamental frequency f0 in periodic sound waves such as musical tones or vowels in speech; their spectrum consists of f0 and its harmonics. Temporal variation of f0 results in melody in music and intonation in speech. Timbre represents a specific distribution in the intensities of f0s and its harmonics in the spectrum. Two renditions of the same tone from two different musical instruments, having the same f0, will have different timbres due to the difference in the relative intensities of particular harmonics (the spectral envelope), and as a result, they will sound different [ 22 ]. If a sound spectrum does not contain just harmonic tones (f0s and their harmonics), the spectrum is not discrete; sound spectrum is rich with frequency components in parts or in the entire frequency range of the human auditory sense. Such sounds, with a spectrum that is more or less continuous, are much more frequent in nature (e.g., noise of a car or a machine or any transient noise). Magnitudes of spectral components contribute to the loudness; sound pressure level is defined in dB relative to the threshold of hearing at 1 kHz (20 µ Pa) and has range 0–120 dB to the threshold of pain [ 17 , 22 ]. To conclude, two sounds can be separated from each other in an auditory scene analysis according to the differences in loudness, pitch (f0, if present), and timbre or spectrum as a whole, as well as in their temporal and/or spatial variations that can create a variety of sound impressions.

Acoustic signals are received by a listener and transformed into linguistic and nonlinguistic categories, but it is not known exactly how. There is ongoing research on neurophysiology of speech communication using the latest advances in invasive and noninvasive human recording techniques, with the aim to uncover fundamental characteristics of cortical speech processing [ 16 ]. The research team in question has studied phonetic feature encoding and mechanisms of noise robust representation of speech in auditory cortex based on the evidence that humans and animals can reliably perceive behaviourally relevant sounds in noisy and reverberant environments.

Neuro-inspired computational models try to provide progress in artificial deep neural network (DNN) performance, based on better understanding of the representation and transformation performed by these models. A case study in ASR given in [ 33 ] attempts to identify the mechanisms that normalize the natural variability of speech and compares these mechanisms with findings of speech representation in the human auditory cortex. The aim is to compare DNNs with their biological counterparts, identify their limitations, and reduce the performance gap between biological systems and artificial computing. For example, a human is able to concentrate on one speaker voice and ignore other sounds and voices [ 23 , 31 ], based on their differences in spatial positions, pitch, and timbre, coherence of changes in level and/or frequency, and time characteristics (onset/offset asynchrony) [ 30 ]. An algorithm aimed at focusing on one speaker in a group of many speakers based on deep attractor network is proposed in [ 34 ], based on similar principles. It has been shown that switching attention to a new speaker instantly changes the neural representation of sound in the brain. An adaptive system should change the sensory representation in real time to implement novel, task-driven computations that facilitate the extraction of relevant acoustic parameters.

Human listeners have a remarkable ability to understand quickly and efficiently the world around them based on behaviour of known sound sources. Moreover, they are able to pay attention and focus on the meaning of speech of a particular speaker. Attentional focus can be integrated into HCI dialogue strategy [ 35 ], while data related to human cognitive effort can be used in postprocessing and improvement of the performance of ASR systems [ 36 ]. Humans are able not only to separate one speaker or concentrate only to one sound source but also to group more sound sources and hear, e.g., the entire orchestra as one musical sound based on harmonicity and synchrony of particular sound sources. Concurrent and sequential grouping processes are described in more details in [ 37 ].

The role of the nonlinearities in DNN in categorization of phonemes by their nonuniform and nonlinear warping of the acoustic space are studied in [ 38 ], as well as the way perceptual invariant categories are created. Biological neurons are able to dynamically change the synaptic efficacy in response to variable input conditions. It is called synaptic depression and when it is added to the hidden layers of a DNN trained for phoneme classification, ASR system becomes more robust to noisy conditions without explicitly being trained for them. The results from [ 39 ] suggest that more complete neuron models may further reduce the gap between the biological performance and artificial computing, resulting in networks that better generalize to novel signal conditions.

2.3. Engineering vs. Linguistic Point of View to NLP as a Typical AI Topic

The mechanism of speech production and the physical component of sound perception are relatively well-studied topics [ 22 , 31 ], while cognitive aspects of speech communication still represent a widely open research area. All aspects of human-machine speech communication that are related to linguistics, such as natural language processing (NLP), cognitive sciences—neurolinguistics, and dialogue management (see Figure 1 ), represent great challenges to the scientific community. In the recent past, the development of speech technology and spoken dialogue systems has gained most momentum from the engineering disciplines, through the possibility of automatic learning from vast quantities of data, in terms of development of computational facilities, complex learning algorithms, and sophisticated neural model architectures addressing particular phenomena and problems of cognitive linguistics. At the same time, cognitive speech sciences mostly remain outside of the scope of the immediate interest of engineering disciplines relevant to speech technology development. Nevertheless, the knowledge in these areas overlaps in the concept and scope with machine learning, which, inspired by neurosciences, has brought about progress not only in human-computer interaction and computational linguistics but also in the area of spoken language processing, which lies in their intersection. This is indicated in Figure 1 , which also shows a relatively wide gap between cognitive sciences (neuroscience) and psycholinguistics on one side and predominantly engineering disciplines on the other.

As regards the role of machine learning in the development of speech technology, it has offered a powerful alternative to models dependent on linguistic resources and modules performing particular linguistically motivated subtasks. Linguistic resources such as dictionaries and speech databases are typically quite expensive and time-consuming to collect and annotate, while the development of modules that compose a speech technology system requires deep domain knowledge and expert effort. In the last two decades, some of the tasks performed by rule-based systems or simpler machine learning methods have, one by one, been overtaken by neural networks. Namely, in the case of acoustic speech recognition, neural networks have been shown to outperform hidden Markov models (HMMs) in acoustic modelling [ 40 ] but have also outperformed classical N -gram language models in terms of generalization, using either architectures based on long short-term memory (LSTM) neurons [ 41 ] or recurrent neural networks (RNN) [ 42 ]. Solutions based on neural networks have been shown to reach human parity in tasks as complex as casual conversational speech recognition [ 43 ]. In combination with a range of data-synthesis techniques for obtaining large quantities of varied data for training, it is now possible to obtain an end-to-end ASR capable of outperforming state-of-the-art pipelines in recognizing clear conversational speech as well as noisy one [ 44 , 45 ]. They have also been used in multimodal speech recognition, i.e., recognition of speech from audio and video [ 46 ]. The task of speech synthesis is a more language-dependent one, and in that it is more challenging since it aims to reintroduce the redundancy which is lost when speech is converted into text, and to do it in such a way that, among a multitude of prosodic renditions of a particular utterance, it produces one that the listener will consider acceptable in a given context. Here again, neural networks have shown to overperform classical models working on parameterized speech such as HMMs [ 47 , 48 ] in acoustic modelling, and they have also been employed for prosody modelling [ 49 ] as well as modelling of acoustic trajectories [ 50 ]. Neural networks have also addressed the problem of a somewhat muffled character of synthesized speech due to the use of a vocoder, by performing synthesis of raw speech waveforms instead [ 51 ]. Finally, to overcome the need for sophisticated speech and language resources that require deep domain expertise, a range of end-to-end architectures were proposed, with the ultimate end that the system should be trained on pairs of text and audio, exploiting the capability of neural networks to automatically develop higher-level abstractions [ 52 ]. The flexibility of such a powerful data-driven approach in comparison with classical speech concatenation synthesizers has also brought significant progress in the area of multispeaker TTS and speaker adaptation [ 53 – 55 ] as well the ability to conform to a particular speech style or emotion [ 56 ]. This is particularly relevant as it coincides with the emergence of applications such as smart environments, virtual assistants, and intelligent robots, demanding high-quality speech synthesis in different voices and different styles and conveying different emotional states of the perceived speaker [ 57 ]. Other language technology tasks have also been successfully addressed by neural networks, such as question answering [ 58 ], text classification [ 59 , 60 ], machine translation [ 61 , 62 ], and sentiment analysis [ 63 ]. Neural networks have also been used as a powerful linguistic tool, for modelling sentence syntax [ 64 ] or exploring particular linguistic phenomena such as establishing word representations in vector spaces [ 65 ]. However, rather than providing a decomposition of the problem and a clear analytical insight into it, neural networks provide an alternative, data-driven point of view, and thus cannot be considered a classical tool of theoretical linguistics. On the other hand, their performance in solving these problems justly makes neural networks state of the art in the development of speech technology.

3. Progress in Speech Recognition and Synthesis, as well as Dialogue Systems

Apart from automatic speech recognition (ASR) and text-to-speech synthesis (TTS), a human-machine speech dialogue system also includes a dialogue management module with corresponding dialogue strategies and language technologies for spoken language understanding (SLU) and spoken language generation (SLG), as illustrated in Figure 4 .

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Components of a human-machine speech dialogue system.

This section presents some achievements in the field of speech technologies such as ASR and TTS. They have been developed with an effort to combine interdisciplinary knowledge from different areas such as linguistics, acoustics, computer science, and mathematics. Signal processing engineers usually have integrating roles among linguists from one side and mathematicians from the other side.

3.1. Progress of Automatic Speech Recognition Systems

Research and development of ASR systems began in the 1950s in Bell Labs, with simple digit recognition systems, and since then the recognition tasks have become more complex—from the recognition of isolated digits, then isolated words, then continuously spoken words in a silent environment, up to the recognition of spontaneous speech in a noisy environment. Consequently, the complexity of the algorithms used also increased drastically. A brief review of historical development of ASR can be found in [ 66 ]. There were three important moments in the development of ASR systems: introduction of mel-frequency cepstral coefficients [ 67 ], introduction of statistical methods (hidden Markov models (HMM) with Gaussian mixture models (GMM)) [ 68 ], and introduction of deep neural networks (DNN) [ 69 ]. This development was also supported by the technological development in the computer industry as well as the increase in the amount of data available for training these systems.

The domination of DNNs in ASR started with [ 40 ], which showed that feedforward DNN outperforms GMM in the task of estimation of context-dependent HMM state emitting probabilities. For a small database, such as English Broadcast News (about 30 h of training data), the difference in word error rates (WER) was not significant, but for the Switchboard database, which is bigger (about 300 h of training data), the difference became substantial. Further improvement of DNN was based on better optimization, new activation functions, new network architectures, new speech preprocessing methods, and leveraging multiple languages and dialects [ 70 ]. One of the important findings was that layer-by-layer pretraining using restricted Boltzmann machines (RBM) is not obligatory and that backpropagation algorithm is sufficient for training in case of a large quantity of available training data as well as a large number of units in the hidden layers. Additionally, LeCun et al. showed in [ 71 ] that in case of sufficiently wide DNN (large number of units in a layer), there is no problem with the local minima and that the values of local minima are very close. The next big step was a complete elimination of HMM from the model. Graves and Jaitly in [ 72 ] reported a speech recognition system that directly transcribes audio data with text, without requiring an intermediate phonetic representation. The system is based on a combination of the deep bidirectional long-short term memory (LSTM) recurrent neural network architecture and the connectionist temporal classification (CTC) objective function. Such a direct mapping of an audio signal into a grapheme sequence allows easy application of the system on new languages such as Serbian [ 73 ]. Inspired by CTC, Povey at al. in [ 74 ] developed lattice-free maximum mutual information using phone n -gram language model starting from randomly initialized neural networks. This method was also successfully applied to Serbian [ 75 ]; i.e., the relative reduction of WER was about 25% with respect to the best previous system.

3.2. Progress of Speech Emotion Recognition

Since humans are not always rational and logical beings—emotions play very important aspects in acceptance of new products and technologies [ 76 ]. The earliest attempts to recognize speaker emotional state on the basis of voice characteristics date back to the 1980s [ 77 ]. The initial motive for this research direction was the adaptation of an ASR system to emotionally stressed speech [ 78 ], but another motive appeared with the development of spoken dialogue systems, where it was useful to modify the dialogue strategy based on, e.g., user annoyance [ 79 ]. There are a number of emotions that can be easily represented in the activation-evaluation space [ 80 ], but classification of such a large number of emotions is difficult. Hence, classification space has been reduced to neutral and 6 archetypal emotions: anger, disgust, fear, joy, sadness, and surprise, which are the most obvious and distinct emotions [ 80 ]. It should be noted that archetypal emotions are not primary emotions in so-called “pallet theory,” where each emotion can be represented as a combination of the primary ones.

One of the important steps in the design of a speech emotion recognition system is the extraction of features that efficiently discriminate between emotions independently of lexical content, speaker, and acoustic environment. It is well known that prosodic features are correlated with emotions [ 80 ], which is why standard features used in emotion recognition systems include pitch, energy, and phone duration [ 81 ]. These features are also related to the voice quality that is related to the emotions [ 82 ]. Emotions affect speech energy distribution across a wide range of frequencies, thus spectral features such as MFCCs, linear prediction cepstral coefficients, log frequency power coefficients, and formants were further proposed [ 83 , 84 ]. Feature extraction procedure starts with the segmentation of the input signals into 20–30 ms long frames shifted by 10 ms, since speech is a nonstationary signal. After that, the features extracted from a chosen segment (corresponding to a particular phoneme, syllable, word, or sentence) are mapped into a single vector using functionals such as mean, second moment, contour slope, and range. Hereafter, features “condensed” in such a way represent the input of standard classification algorithms such as linear Bayes [ 85 ], k nearest neighbours [ 85 , 86 ], support vector machines [ 87 ], GMM [ 86 ], and artificial neural networks [ 88 ]. On the other hand, such frame-based features can also be classified as a sequence using HMM [ 84 ] and RNN [ 89 ]. Besides low-level acoustic features, individual words or sequences of words obtained by ASR can also be used to perform emotion classification [ 90 ]. After a huge success of convolutional neural networks (CNN) in image classification, where lower layers of the network perform feature extraction, some research groups have tried to implement CNN in the same manner to obtain features [ 91 , 92 ]. Since speech emotion recognition is a scarce data problem, one of the future trends will be the application of semisupervised learning [ 93 ]. More details about features, classification algorithms, and databases can be found in [ 94 – 97 ].

3.3. Progress in the Development of Text-to-Speech Synthesis

The very first “speech machines” were mechanical devices capable of producing single phonemes, and some of their combinations were introduced by Christian Kratzenstein and Wolfgang von Kempelen at the end of eighteenth century [ 98 ]. The VODER, presented in 1939 by Homer Dudley, can be considered as the first synthesizer which could generate whole sentences [ 99 ]. The first full TTS system for English was introduced in 1968 by Teranishi and Umeda [ 100 ]. It was an articulatory-based system which could perform text analysis and determine pauses in text using a sophisticated parser [ 101 ].

However, it was not until concatenative synthesizers were invented, that TTS gained widespread usage. The idea of concatenative TTS is to concatenate appropriate parts of a prerecorded database [ 102 ]. If the goal is domain-specific synthesis or a very large speech database is available, this approach can produce high-quality speech. However, there are audible glitches at the concatenation points if the appropriate units cannot be found in the database. The method is also extremely inflexible in terms of changing the speaking style or the voice of the speaker; it requires a whole new database to be recorded and annotated.

As applications of TTS became more popular and more widely used, the necessity of algorithms that could produce different voices and speaking styles from smaller databases has grown. From around 2000, statistical parametric speech synthesis, where the spectrum, fundamental frequency, and duration of speech were modelled by multispace probability distribution HMMs and multidimensional Gaussian distributions [ 103 ], became popular. The HMM synthesis enables transformation of speaker-independent system toward a target speaker using a very small amount of speech data [ 104 ], creating expressive voices [ 105 ], as well as multilingual voices [ 106 ]. However, this method never achieved the naturalness of concatenative TTS. One of the main problems is the signal smoothness caused by modelling similar contexts with the same Gaussian mixtures. Another big problem introduced with parametric methods is the usage of vocoder, a system that produces speech waveforms from predicted acoustic features. Vocoders, although significantly improved over the time, introduce some artefacts which affect the overall quality of generated speech. A detailed review of HMM-based speech synthesis can be found in [ 107 ].

The first attempts to use neural networks in speech synthesis can be found in [ 108 ]. However, the recent development of hardware, especially graphical processing units (GPUs), has popularized this approach and established its dominant status in the TTS research society. Deep neural networks (DNN) replaced decision trees and Gaussian mixture models in mapping input linguistic features to output acoustic features, enabling nonlinear mappings [ 109 ]. Although simple feedforward NN with several hidden layers and sigmoid or tangent hyperbolic activations are sufficient for the production of intelligible and natural sounding synthetic speech, introduction of LSTM (long short-term memory) units has brought further improvement into the quality of synthesized speech [ 110 ]. Some improvements were also reported by introducing generative adversarial networks [ 111 ] and stacked bottleneck features [ 112 ].

DNNs have not only just enabled generating synthetic speech of high quality but also introduced many possibilities for production of speech in different voices and speaking styles. A majority of methods for creating new DNN voice using limited amount of training data is based on usage of multispeaker models. In multispeaker modelling, a large database consisting of multiple speakers is required. Each speaker is usually represented with less data than in case of single-speaker modelling. Due to a variety of contextual information and better network generalization, the quality of speech produced with multispeaker models is similar or even better than speech obtained with single speaker models. Speaker identity in multispeaker systems can be represented in several ways. One group of approaches is based on the use of a unique vector for each speaker. This vector can be represented as i vector [ 113 ] or just one-hot vector [ 54 ] and is used in training as extension of standard input or additional input to any of the hidden layers. Another group of methods for representing speaker identity is based on splitting network to speaker-specific and shared parts. In [ 53 ], separate output layers for each speaker have been introduced. In [ 114 ], even language-dependent parts of the network have been added, but this approach requires data from the same speaker in multiple languages. Creating a new voice, whose samples have not been seen in the training phase, in a multispeaker framework is based on adapting only the speaker-dependent part of the network [ 53 ], estimating the speaker-specific vector for the new speaker [ 55 ] or adjusting the parameters of neurons in starting models [ 113 ]. As opposed to the usage of multispeaker models as starting models for adaptation, in [ 115 ], adaptation starting from a single speaker model is investigated. It has been shown that only ∼10 min of target speaker voice is required in order to produce synthetic speech in target speaker's voice reaching the quality of conventional methods built on several hours of speech database. The hypothesis was that the models of speakers A and B are more similar than a randomly initialized model and the model of speaker B, consequently requiring less data to train the model of speaker B starting from the model of speaker A than starting from a randomly initialized model.

Synthetic speech should convey not only just information but also paralinguistic information such as emotional state. There is also a need to support some task-specific speech styles such as news, commercials, storytelling, and warnings [ 116 ]. It has been shown that emotion, mood, and sentiment affect attention, memory, performance, judgement, and decision-making in humans [ 117 ], which supports the necessity of using different speaking styles in synthetic speech for many applications. Three different methods for style modelling are compared in [ 118 ]. The presented methods are based on ideas introduced in multispeaker modelling using input codes, network adaptation, and separated output layers. It has been shown that only ∼5 min of speech per style is sufficient in order to produce speech of acceptable quality in a specific style. Using input codes for representing different styles is also presented in [ 119 , 120 ]. There have also been attempts at style transplantation, i.e., producing speech in the voice of speaker A in style X without having any sentence from speaker A in style X in the training data, in which case the network is forced to learn the style X from other speakers in the training database [ 121 , 122 ].

Although DNNs have shown to be extremely powerful and flexible, for a long time, one of their main disadvantages in speech synthesis has been their dependence on the usage of a vocoder. For the first time in 2016, raw audio samples were directly predicted by DNN using WaveNet architecture [ 51 ]. This model is fully probabilistic and autoregressive, with the predictive distribution for each audio sample conditioned on all previous ones. When conditioned on linguistic features derived from text and speaker identity, it can be used as TTS and it significantly outperforms all other TTS systems. The main drawbacks of this system are its need for extremely large databases and extreme computational power, although the synthesis has since been accelerated by the introduction of approaches such as Parallel WaveNet [ 123 ]. A similar model called DeepVoice was introduced in 2017 [ 124 ]. In DeepVoice, every part of TTS pipeline is replaced by a corresponding DNN. Its main drawback is the fact that all components of TTS system are trained independently, and it leads to a cumulative error in synthesized speech in the end.

As opposed to WaveNet and DeepVoice systems, which use lexical features as inputs, there are systems which use raw orthographic text as input, such as Tacotron [ 52 ], Tacotron 2 [ 125 ], and Deep Voice 3 [ 126 ]. Tacotron outputs spectrograms that are transformed to speech samples using Griffin–Lim algorithm, which also introduces artefacts in generated speech. On the other hand, the Tacotron 2 system-generated spectrograms are used for conditioning standard WaveNet architecture, which generates speech samples. DeepVoice 3 architecture can output spectrograms or other features which can be used as input to some waveform synthesis models. Adaptation to new speakers has also been investigated in end-to-end systems [ 127 , 128 ] as well as synthesis in different styles [ 129 , 130 ].

The main advantage of an integrated end-to-end TTS system is that requires minimal human effort since there is no need to label input data. Since in end-to-end systems, direct sample values are often predicted [ 29 ], the usage of 16 bit samples would make the prediction complicated and some type of quantization is performed. For this reason, improved coding and compression algorithms are important for TTS.

3.4. Dialogue Systems

Automatic speech recognition and speech synthesis are technologies with a long history. During the last five decades, a wide spectrum of algorithms shaped our knowledge within the speech technology field. With the recent advances in the world of deep learning and artificial neural networks, we are able to imitate to some extent the human auditory system sensitivity, recognition accuracy, human voice intelligibility and naturalness, emotions in synthesized speech, etc. As the result, machines are able to identify particular speakers, recognize human words in a noisy environment or to perform large-vocabulary continuous speech recognition with high accuracy. Furthermore, with a small amount of speech data from target speakers, they synthesize high quality speech, good enough to become a threat to automatic speaker verification systems.

One question that naturally arises is whether this is enough to achieve intelligent-like, natural and long-term human-machine speech interaction. Unfortunately, it is not.

Speech recognition and synthesis are only two of the six modules in a typical architecture of a speech dialogue system, depicted in Figure 4 , and each of the six modules corresponds to certain cognitive aspects underlying the human language processing system. As a result, dialogue management becomes a complex structure that involves cooperation of several, quite different functional units. Leaving aside the division of dialogue systems into task-oriented and non-task-oriented, we must emphasize that the biggest challenge scientists face during the research in this area is to emulate human ability to understand meaning and conduct a conversation that is forward-looking, informative, and coherent. Regarding the dialogue initiatives, machines are successful in handling conversations that are system initiative (or single initiative). In such cases, the system completely controls the conversation and maintains the processes of speech recognition, meaning extraction, answer generation, and speech production. However, as it is known, natural dialogue is not deterministic and real improvements in human-machine speech interaction can be achieved only if adaptive behaviour with respect to the intention, the current context, and history of interaction are provided.

As a traditional paradigm shift, recent works in this area have addressed a series of data-driven, end-to-end trainable, non-goal-driven systems based on generative probabilistic models [ 131 ]. As such, these models can be viewed as artificial cognitive systems, aimed at grouping and carrying out traditional dialogue management tasks: language understanding, reasoning, decision-making, and natural language generation. They are corpus-based, data-driven dialogue systems, based on machine learning algorithms using corpora created from real word data. The statistics observed in dialogue corpora is the main knowledge for the optimization of parameters and variables.

It is worth pointing out that, besides the importance of domain knowledge, linguistic context has the crucial impact for active and engaging conversation. However, one of the main drawbacks of these approaches is related to sparsity issues that can be expected during integration of contextual information into statistical models. In the work of Sordoni et al. [ 132 ], the neural network architecture is used to address this problem, allowing the system to take into account the previous dialogue utterances. While modelling contextual information, the authors identify models for three linguistic entities in a conversation: the context ( c ), the message ( m ), and response ( r ). On that basis, they suggest three context-based generation models to estimate a response r = r 1 ,…, r T as follows:

This work extends the recurrent neural network language models (RNNLM) as a generative model of sentences [ 133 ]. As the basic principle in this neural network model, input vector, representing the current word at time instant t , is concatenated to the output from neurons in network context layer at time t − 1. In order to capture long-span dependencies together with semantic and syntactic similarities, the authors select word embedding as a continuous representation of words and phrases. Similar approaches already advanced classical language modelling, based on traditional n -gram language models [ 134 , 135 ].

In line with this, many researches are trying to take advantage of combining neural network and end-to-end training possibilities with the large amount of freely available text or audio material from social media, movie scripts, etc. [ 136 ]. Serban et al. [ 137 ], for example, demonstrated introduction of latent variables to hierarchical recurrent encoder-decoder architecture. The research presented in [ 138 ] extended the hierarchical structure with the attention mechanism (word level attention and utterance level attention), taking into account that words and utterances in the context are differentially important.

Although end-to-end, statistical models have drawn most of the recent research on dialogue systems, many problems remain unresolved [ 131 ]. Neural network-based models are capable of handling large amount of data, but still it is hard to design an intelligent system based on imitating responses (especially if we take into account that the dialogue data for a specific domain are quite limited). Hence, to reduce these limitations, Mišković et al. [ 36 ] proposed a different, representational approach. This work extends the focus tree model, a cognitively inspired computational model of working memory that allows for adaptive dialogue management in human-machine interaction. The research not only is focused on improvements of speech recognition module but also points to possible new architectural aspect of dialogue systems. Following the assumption of the hierarchical and associative nature of human memory system and facts that the processing of the user's dialogue acts in human-machine interaction is always context-dependent, this model enables, to some extent, understanding of language and real word data.

4. Progress in Speech Signal Compression, Coding, and Transmission

In general, speech coders can be classified into three major categories depending on the applied coding technique: waveform coders, parametric coders, and hybrid coders. The primary idea behind a waveform coder design is to preserve the shape of a speech signal waveform, thus encoding information about the original time-domain waveform [ 4 – 6 , 14 , 139 ]. Such coders are broadly used in embedded applications due to several reasons: low cost of manufacturing, low computational resource usage, and high speech quality [ 4 – 7 , 14 , 139 ]. The simplest and most well-known type of waveform coders is pulse code modulation (PCM) coder, which is considered as a standard in digital telephony. One of the key advantages of PCM coders is that they are instantaneous, implying a coding delay of no more than one sample period [ 4 ]. Unlike waveform coders, which tend to reconstruct the original shape of the speech signal in time-domain, parametric coders reconstruct the speech signal from certain parameters that model the source signal, making no attempt to preserve the original shape of the waveform [ 4 – 7 , 14 , 139 ]. Due to this limitation, parametric coders are more signal dependent and less versatile. Additionally, compared to waveform coders, they provide a lower quality of speech signals. In parametric coders, human speech production mechanism is modelled with a time-varying filter, having coefficients commonly determined by the linear prediction analysis procedure. In the end, hybrid coders represent a class of coders, which combine features of both previously described classes of coders, namely, hybrid coders tend to preserve the shape of the signal in time domain and also exploit perceptive characteristics, that is, parametric approach [ 4 – 6 , 14 , 140 ]. Performance comparison of these three classes of coders is presented in Figure 5 , where mean opinion score (MOS) is used as one of the standard subjective measures of reconstructed speech signal quality [ 4 ].

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Speech signal quality according to MOS versus bit rate for various speech signal coding techniques.

From Figure 5 , one can conclude that waveform coders provide excellent quality of reconstructed speech signal and that they represent the best choice at bit rates higher than 16 kbits/s, whereas parametric coders cannot provide high quality regardless of the bit rate. On the other hand, parametric coders provide much better quality than waveform coders at low bit rates. Finally, hybrid coders are most suitable at medium bit rates. As for the purposes of speech synthesis and automatic speech recognition, the highest possible quality of reconstructed signal is desirable and waveform coders are usually considered as an adequate choice. Thus, what follows is focused on PCM and adaptive PCM (ADPCM) coding techniques.

4.1. Adaptive PCM

Speech signal can be considered as a nonstationary process, whose average power significantly fluctuates in time domain, resulting in a wide dynamic range [ 4 ]. However, speech signal can be considered as almost stationary in a short period of time (up to 30 ms). This means that speech signal has a highly predictable characteristics during short periods of time, which is suitable for utilizing adaptive quantization [ 4 , 8 – 10 , 141 – 147 ]. Commonly, adaptive quantization is frame-based, where frames are formed by dividing an input speech signal into sets of samples.

There are two fundamentally distinct categories of adaptive quantization techniques: forward and backward adaptive quantization techniques [ 141 ]. Forward adaptive techniques require transmission of additional information about the estimated gain, which is used for adaptation. Moreover, forward adaptive techniques require a longer processing delay than backward adaptive techniques as samples within a frame have to be stored in a buffer, in order to estimate predictable characteristics of every frame. When the gain is estimated and the quantizer is adapted, samples can be quantized and further transmitted to the decoder along with the quantized gain.

A general forward adaptive PCM model is presented in Figure 6 [ 8 , 10 ]. The encoder is formed of two parts: a fixed (nonadaptive) part, consisting of a fixed quantizer Q f , and an adaptive part, consisting of a buffer, a gain estimator, one divider, and a fixed gain quantizer Q g . If Q f is a piecewise linear μ -law quantizer designed for 8 bit/sample and μ = 255, the general forward adaptation model becomes a forward adaptive PCM model defined by G.711 standard [ 148 ].

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Forward adaptive PCM: (a) encoder; (b) decoder.

Unlike forward adaptation, backward adaptation does not estimate characteristics of samples in a frame while encoding, which means that there is not additional information that has to be transmitted [ 149 ]. In fact, gain estimation is performed at the receiver after decoding, considering previously quantized samples. The simplest backward adaptive quantization model is based on uniform quantization with one codeword memory exploited for gain estimation and it is commonly referred as Jayant's model [ 4 ].

Advanced backward adaptive models commonly incorporate more sophisticated gain estimation methods, or variance σ ^ y 2 n estimation methods, which, for quantization of a current sample x ( n ), typically exploit a larger number of previously decoded samples y ( n − i ) [ 4 ]:

where α is a weighting parameter, which can take values 0 < α < 1. Parameter α defines a learning period, that is, a time required for variance estimation [ 4 ]:

Equation ( 2 ) can be written in the following recursive form:

which is straightforwardly used in the simplest mathematical model of Jayant's backward quantizer with one codeword memory. One of the realizations of backward adaptive PCM with one codeword memory that incorporates a widely used companding quantization model is shown in Figure 7 , where M ( n − 1) denotes a step size multiplier, used for adaptation, and c ( x ) and c −1 ( x ) are a compressor function and an expandor function, respectively.

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One of the realizations of backward adaptive PCM with one codeword memory: (a) encoder; (b) decoder.

4.2. Dual-Mode Quantization

Dual-mode and adaptive dual-mode quantizers belong to a relatively new class of quantizers whose design is based on multiparameter adaptation, such as variance and maximum amplitude [ 8 , 9 , 11 ]. Depending on their purpose and application, they can perform quantizer adaptation according to the frame variance and to the frame maximum amplitude x max and also according to the subframe maximum amplitude. By utilizing two quantizers, which compose the dual-mode system, and by applying switched technique, it is possible to achieve a better quality of the quantized signal, or a higher compression, compared to the common single-mode quantizers. In Figure 8 , a dual-mode quantization scheme is shown, where Encoder 1 and Decoder 1 are related to the quantizer applied for processing signals having restricted amplitude range, whereas Encoder 2 and Decoder 2 are related to the quantizer applied for processing the signals having unrestricted amplitude range [ 8 , 9 , 11 ]. The switched process is frame-based, and it is performed so that the restricted quantizer is used in the case if all samples within a frame belong to the restricted quantizer's support region, while the unrestricted quantizer is used otherwise [ 8 , 9 , 11 ]. The main idea behind such quantization model is to enable a more preferable selection of the restricted quantizer, with a narrower support region, than the unrestricted one, since, in such a manner, an increase of the signal to quantization noise ratio can be provided.

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Dual mode quantization scheme: (a) encoder; (b) decoder.

Considering that speech signal can be described using Gaussian probability density function (PDF) or Laplacian PDF, which is heavy-tailed, it is expected that only small percentage of speech frames will have some samples of large values. However, this also depends on the size of a frame. Consequently, the support region threshold values for both quantizers should be chosen so that the restricted quantizer usage should be dominant, but taking also into account the frame size and the whole input signal dynamics in order to achieve a minimum of the total distortion introduced in the quantization process [ 8 , 9 , 11 ].

4.3. Differential Pulse Code Modulation

Differential pulse code modulation (DPCM) represents a simple but high-quality speech signal coding scheme for middle bit rates. It initially exploited uniform quantization and the first-order prediction [ 150 , 151 ]. As it was already discussed, speech signal has highly predictable characteristics within a frame, which is exploited to reduce the dynamic range of amplitudes for quantization in the DPCM scheme [ 4 , 12 , 13 , 152 , 153 ]. In particular, DPCM predicts the next sample amplitude value and encodes the difference between the predicted value and the value of the current input signal amplitude. Due to the high correlation, these differences have much smaller values compared to ones of the input signal samples, so that the dynamic range of amplitudes is significantly reduced before quantization. Accordingly, with a suitable design of a DPCM system, a certain distortion may be provided at lower bit rates compared to the PCM system. In other words, a worthy compression may be achieved with the DPCM system compared to the PCM.

More sophisticated solutions may incorporate prediction of a higher order or other kinds of quantization models, such as a gain-adaptive quantization model [ 154 ]. Figure 9 shows a DPCM scheme with incorporated simple first-order predictor and forward gain-adaptive quantizer based on optimal companding model [ 151 ].

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DPCM: (a) encoder; (b) decoder.

In the DPCM system given in Figure 9 , the reconstructed speech signal x ^ is determined by

where y a denotes the output of the adaptive quantizer, whereas n denotes the n -th sample of the signal. It can be noted that the value of parameter a depends on the nature of the input signal. If an input signal is highly correlated, it is preferred to use values close to 1 (e.g., a = 0.8), whereas values close to zero are preferred for lowly correlated signals (e.g., a = 0.3). However, the choice of parameter a is not an easy task even if adaptation is applied. The determination of linear predictor coefficients can be done using methods that are based on statistical learning such as least mean squares (LMS) estimation method [ 155 ]. LMS search algorithm reduces distortion by adapting coefficients for each input sample, and its main features, which attract researches, are low computational complexity, proof of convergence in stationary environment, unbiased convergence in the mean to the Wiener solution, and stable behaviour when implemented with finite-precision arithmetic [ 156 ]. Moreover, coefficients of linear predictor as well as determination of other important parameters for quantizer design may be determined by exploiting artificial neural networks or regression methods.

5. Conclusions

This review article has provided an overview in the recent development of speech technologies and other scientific areas related to them, mostly due to the development of the new machine learning paradigm, which has had a tremendous impact in this domain. Apart from natural speech production and speech perception, understanding of cognitive aspects of speech communication is very important for future HCI systems including both spoken language understanding and generation as language technologies. The machine learning paradigm has had a great impact on automatic speech recognition (ASR) and text-to-speech synthesis (TTS) as basic speech technologies. It is expected that ASR systems based on deep learning and adaptive algorithms in the near future will be able to recognize spontaneous speech in complex acoustic environments, with the accuracy that will surpass the corresponding ability of humans. Synthetic speech has already reached such quality that is hard or impossible to differentiate from human speech. With flexibility of changing speaker and style, HCI is becoming as pleasant and natural as human-human interaction. Unsupervised and reinforcement-based machine learning algorithms will also develop further, which will, in turn, bring about progress in areas where large data sets are not available, as is the case in speech analysis for speech recognition and synthesis for under-resourced languages. A short overview of speech coding techniques and of current progress in adaptive scalar quantization has been presented as the quality of digitized and compressed speech signal is important for accurate automatic speech signal detection and synthesis. Although these techniques can be designed to be robust in a wide dynamic range of speech signal variations, or to be frame-adaptive, one can anticipate that machine learning tools of increasing popularity will lead to novel solutions, which will improve performances of various systems by adapting predictive coefficients. To conclude, we are witnessing an increasingly fast progress in the field of speech signal processing due to machine learning paradigms, and it appears very hard to predict what they will bring about next and how soon that can be expected.

Acknowledgments

The work described in this paper was supported in part by the Ministry of Education, Science and Technological Development of the Republic of Serbia, through the project “Development of Dialogue Systems for Serbian and Other South Slavic Languages” (TR32035).

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

1 Minute Speech on Technology and Development in English

Respected Principal, teachers and my dear friends, a wonderful morning to all of you. Today on this special occasion, I would like to speak some words on the topic- Technology.

Technology refers to machines, devices and scientific knowledge that makes life easier for us. In recent times, humankind has seen unprecedented scientific progress. As a result, technology has taken over every aspect of our lives. From cars to mobile phones to television sets, we see technology all around us. It is an indispensable part of our daily routines.

However, technology has many negative effects too. It has caused great harm to the environment, with pollution on an all-time high. It has also led to health problems and feelings of depression and anxiety.

To conclude, we must be careful while using technology, because while it makes our lives easier, it may also have negative consequences if not used in moderation. Thank you for listening to me so attentively.

Random University Name Generator
Raag Darbari Summary & Notes Part 3 by Shrilal Shukla
How Does Homework Help You Be Smarter?
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An Overview of Modern Speech Recognition

Xuedong Huang ,

in Handbook of Natural Language Processing, Second Edition, Chapter 15 (ISBN: 1420085921)

Published by Chapman & Hall/CRC | 2010 | Handbook of Natural Language Processing, Second Edition, Chapter 15 (ISBN: 1420085921) edition

Publication

The task of speech recognition is to convert speech into a sequence of words by a computer program. As the most natural communication modality for humans, the ultimate dream of speech recognition is to enable people to communicate more naturally and effectively. While the long-term objective requires deep integration with many NLP components discussed in this book, there are many emerging applications that can be readily deployed with the core speech recognition module we will review in this chapter. Some of these typical applications include voice dialing, call routing, data entry and dictation, command and control, and computer-aided language learning. In this chapter, we provide an overview in Section II of the main components in speech recognition, followed by a critical review of the historically significant developments in the field in Section III. We devote Sections IV to speech recognition applications, including some recent case studies. An in-depth analysis of current state of speech recognition and detailed discussions on a number of future research directions in speech recognition are presented in Sections V.

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Supported by

David Brooks

Why Is Technology Mean to Me?

an illustration of an angry-looking paper clip

By David Brooks

Opinion Columnist

It is never easy to re-examine one’s fundamental convictions, but now I am forced to question my previous disbelief in the existence of Satan. I am compelled to confront this ugly possibility by the fact that from time to time my electronic devices seem to fall under demonic possession.

Now, I should start by saying that I am not someone with a natural animosity toward personal technology. I have been known to be completely reasonable when the supermarket self-checkout machines refuse to let me proceed until I place my last purchased item into the bagging area. I patiently explain, sometimes with dramatic physical re-enactments, that, in fact, I have placed the product directly in the center of the bagging area, and even into a bag itself.

Despite these kinds of sympathetic efforts, technology finds me wanting; I am disfavored within the silicon-based community, and the situation has become so bad that it’s brought to mind this possibility of a malevolent presence — Beelzebub, Lucifer, the Dark Lord, whatever you want to call him.

Let me describe the events of last Friday, when technology was especially mean to me. I woke up in Chicago to find that my phone, which normally charges through the port on the bottom, was no longer accepting charges from that entry point. I didn’t think much of it, assuming I could clean out some dust or something.

Then I tried to pair it with my earbuds, which it usually automatically pairs with. Nothing doing. This sometimes happens, so I tried connecting it with my backup earbuds, the ones that sound like they’re beaming music from the bottom of the Pacific. These devices also refused to be on speaking terms. I went to the Bluetooth page on the phone, and it was just a bunch of “not connected” readings.

I did what any master technologist would do. I rubbed the earbuds against my phone in a seductive circular manner that I thought might foster a rapprochement. I put them in my ears and grazed the phone against my cheeks with a pressure that was amorous and gentle, but also firm. Still, the phone and earbuds refused to sync. People talk a lot about artificial intelligence but not enough about artificial obstinacy.

As I rushed to the airport my Find My app rubbed salt in the wounds by telling me I had left behind the earbuds that my phone refused to recognize in the first place. At the airport it occurred to me that I might clean the charging port by using a suction technique. So if you were at Midway International Airport last Friday and a small child asked you, “Why is that man sucking on his phone?” that man was me.

I got on the plane, secure in the knowledge that Southwest has very reliable Wi-Fi service. But the flight attendant informed us that this time it wasn’t working, because, you know, Satan. I got home and found my home Wi-Fi wasn’t working, either. I fixed it by turning it off and on, a maneuver that shows, as the Silicon Valley types would say, that I am “tech savvy.”

While at home I had to print six documents. I used to have a printer that served me well until one day it decided my ink cartridges were “corrupt” and refused to do any further printing. I bought more cartridges from the printer’s manufacturer, but my printer still saw shadiness in all new cartridges — like QAnon members looking at national politics.

We bought a new printer, but it’s snooty. Asking it to print something is like applying to Harvard. It was willing to print out an essay from the journal Daedalus and an academic paper on aging, but it was unwilling to print four other documents from mere newspapers and websites. Like Bartleby the Scrivener, it would prefer not to.

You might be reading this account thinking that I’m the problem here. I’m just a technology idiot who doesn’t know how to fix things. I am open to this possibility. When I last went shopping for a car and the salesman started explaining the amazing electronic features on the new models, I was unable to follow him after 0.7 second. But I remind you of the central reality. Gizmos that were working for me one minute stopped working the next. I want my technology to have many capacities, but free will is not among them.

As I’m writing this sad tale my computer is alerting me that I have to shut it down for a vital security update, as it does frequently when I’m on deadline. For a decade, if I deleted an email on my phone it was also deleted on my laptop, but one day that stopped working, too. Every time I log onto my bank’s website, using the same computer each time, I get an email telling me a new device has been detected. And don’t even get me started on subjective security questions. How am I supposed to remember what my favorite pizza topping was 15 years ago when I opened that account? People grow and change.

I am thinking of finding a priest who can do a full-scale technological exorcism — like in that old Linda Blair movie. Before I do, let me just send this off to my editor before my computer crashe$^%#&*((@”+!%#.

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

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David Brooks has been a columnist with The Times since 2003. He is the author, most recently, of “How to Know a Person: The Art of Seeing Others Deeply and Being Deeply Seen.” @ nytdavidbrooks

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6 Windows features that are going away in 2024

Support for 32-bit Arm apps will finally be dropped in the Windows 11 2024 Update.
Classic Windows Speech Recognition is being replaced with Voice Access for easier voice control in Windows 11.
Windows Mixed Reality is also biting the dust this year.

Microsoft is constantly updating Windows 11 , adding all sorts of new features, like Copilot and other AI tools. However, for every feature that's added, there are also many times that features get deprecated or removed altogether, often leaving users and fans upset.

2024 is going to be a big year for Windows, with Windows 11 version 24H2 bringing big changes, but it's also a bit of a bloodbath for existing Windows 11 features. Here are some of the tools and capabilities going away this year.

Windows 11 2024 Update: What's new and why it's not Windows 12

Support for 32-bit arm apps, say goodbye to your windows 8 apps.

The industry has been moving away from 32-bit Arm apps for many years now, and in 2024, Microsoft is finally officially dropping support for them in Windows 11, too. There hasn't been a 32-bit Arm processor for Windows PCs since the Windows 8 era, and by now, any apps that haven't been recompiled for 64-bit are probably just abandoned.

That means there likely isn't much being lost here. Metro apps back then were never all that popular, and any Arm apps that do exist today are already made for Arm64. Still, it might be a bummer if you still have very old apps installed on your PC for whatever reason.

Steps recorder

Just use snipping tool.

Steps recorder was a useful tool in Windows that allowed you to record steps on your computer, so you could give someone else instructions to do something. Steps weren't recorded as a video, but rather, a series of images taken for every interaction made with your PC. It also allowed you to add comments to each step.

With Steps Recorder going away, a possible alternative is to use the Snipping Tool, which is also built into Windows 11. Snipping Tool recently added support for video recording, so it can serve a similar purpose.

It's not completely confirmed that Steps Recorder will be removed this year, but it's officially deprecated and Microsoft started showing a banner to users in early 2024, so it's possible.

Windows 11 deep dive: Checking out the new Snipping Tool

Windows speech recognition, say hello to voice access.

Another feature that's going away is the classic Windows Speech Recognition. This was a tool that allowed you to control your PC using your voice, but in 2022, Microsoft introduced a modernized alternative called Voice access.

This new experience features an improved tutorial for getting started, a list of all the available commands to make it easier to learn, and it has a modern UI that fits right into Windows 11. You're not really missing much with the classic tool going away.

Windows Speech Recognition is another one that isn't totally guaranteed to be removed in 2024, but it was announced to be deprecated right at the end of 2023, so there's no reason you should still be using it anyway.

How to set up voice access on Windows 11

It's all or nothing.

WordPad is arguably the first big loss on this list, because it did kind of fill a void. WordPad is a text editor that lives somewhere between Notepad and Microsoft Word. It's a free tool, but it provides some text formatting options so you can still write a somewhat professional-looking document, albeit with a lot of limitations compared to Word.

It seems like Microsoft wants you to either stick to Notepad or pay up to get access to Word, which probably makes business sense. You can do a lot more with Word, and the web version of the app is free, as long as you have internet. WordPad has been confirmed to be removed with Windows 11 version 24H2 later this year.

Windows Mixed Reality

A remnant of the windows 10 era.

Remember when Windows 10 launched and Microsoft was convinced that mixed reality was the next big thing? Well, while the concept is still being supported in some ways (with the Apple Vision Pro being a big example), Microsoft hasn't really done anything with it on Windows for a few years. To be fair, there also haven't been any new Windows Mixed Reality headsets in all that time, and so Microsoft is calling it quits.

You shouldn't confuse Windows Mixed Reality with Microsoft's HoloLens headset, which runs Windows Holographic. This is a different platform, and it's still being supported for HoloLens owners (even though HoloLens seems to have fallen by the wayside, too).

Windows Mixed Reality has similarly been confirmed to be removed from Windows 11 with version 24H2. If you have a headset, though, you can keep using it with Steam apps, as long as you don't install the update.

Windows Subsystem for Android

Android apps, we hardly knew ye.

Finally, we have the big one. One of the headlining features of Windows 11 when it was first announced was support for Android apps, though it ended up making its debut a few months later, at the start of 2022. Well, just two short years after that launch, Microsoft announced that it was killing off the platform, effective immediately.

The Windows Subsystem for Android isn't just going away this year, it's already gone. The only way to (officially) get Android apps now is if you already have them installed, but if you're setting up a new PC, you no longer have that option. And by this time next year, the feature will be removed entirely.

Thankfully, there are alternatives for running Android apps, such as Bluestacks or streaming apps from your phone with tools like Phone Link.

There are reasons to be excited

It's certainly sad to see Windows features being removed, especially ones that were added as recently as the Windows Subsystem for Android was. But the future of Windows 11 is looking pretty positive with version 24H2 and all the features it's adding, especially the rumored AI capabilities. Plus. the upcoming Qualcomm Snapdragon X Elite chipset is set to change the landscape of the laptop market, which is certainly exciting.

Snapdragon X: Everything you need to know about Qualcomm's Arm computing chips

6 Windows features that are going away in 2024

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Speech about Modern Technology [1,2,3,5 Minutes]
Quotes for Speech on Modern Technology. "Technology is just a tool. In terms of getting the kids working together and motivating them, the teacher is the most important.". - Bill Gates. "The advance of technology is based on making it fit in so that you don't really even notice it, so it's part of everyday life.".
Speech on Technology for Students in English
A Short Speech on Technology. A warm greeting to everyone present here. Today I am here to talk about technology and how it has gifted us with various innovations. Technology as we know it is the application of scientific ideas to develop a machine or a device for serving the needs of humans.
Speech on Technology for Students and Children
3 Minutes Speech on Technology. We live in the 21st century, where we do all over work with the help of technology. We know technology as the name "technological know-how". Read Speech on Technology. Also, it implies the modern practical knowledge that we require to do things in an effective and efficient manner.
Speech on Technology
Speech on Technology: Are you looking for an article to know more about the topic 'technology'. ... The assistance of modern technology has enabled us to save it. After the introduction of technologies, things that took hours and days for completion are now getting completed in seconds and minutes. Simultaneously, it is saving our money and ...
Short Speech on Technology for School Students
Check out the best short speech on technology, 1-minute speech on technology, 10 lines for speech on technology, and more. Indian Exams. Engineering Exams. JEE Main Exam; VITMEE Exam; ... Defence Colony, New Delhi, Delhi 110024 Noida. Nagarro, J97F+GP3, Block A, Sector 64, Noida, Uttar Pradesh 201301 London.
Speech On Technology
Short Speech on Technology. Technology is the study and use of the technical properties of materials, science, and nature to develop mechanical, electrical, biological, and information systems that are more effective and facilitate daily life. Technology has existed since the Neolithic Age or before. The optimum use of pre-Neolithic people's ...
TechTalks that Transformed the World: Exploring the Top 5 Technology
Kay's visionary ideas laid the foundation for modern computing devices and inspired the development of laptops, tablets, and smartphones. His speech encapsulated the idea that the future could be shaped by creative minds and technological innovation. 3. Tim Berners-Lee's "The World Wide Web: A Global HyperText System" (1991)
Ideas about Technology
Video playlists about Technology. From powering the planet with untapped clean energy to making climate action go viral, these 10 transformative ideas from the intersection of tech and sustainability are driving positive change — and building a greener future for generations to come. (Curated in partnership with Acura)
How technology is changing language and the way we think about the world
What most people haven't considered is how technologies affect our language and how these changes are affecting the way we speak and even the way we think. One of the key ways we see this is ...
Voice technology for the rest of the world
December 16, 2021. Voice-enabled technologies like Siri have gone from a novelty to a routine way to interact with technology in the past decade. In the coming years, our devices will only get chattier as the market for voice-enabled apps, technologies and services continues to expand. But the growth of voice-enabled technology is not universal.
Speech on Modern Technology
At its core, modern technology is the fruit of human creativity. We have dreamed, we have thought, and we have made. From smartphones to self-driving cars, from artificial intelligence to virtual reality, technology has changed our world in ways we used to only dream of. Modern technology has made our lives easier.
Speech on Technology: 2 Min Speech on Pros and Cons of Technology
Technology is the practical application of scientific knowledge. The use of technology greatly influences our daily lives. Technology, from the alarm clock to the nightlight, has become crucial to our daily survival. Technology has advanced into new fields in our generation. It is continuously improved, and the results get better every year.
Essay on Modern Technology
Speech on Modern Technology; 250 Words Essay on Modern Technology The Advent of Modern Technology. Modern technology, an offshoot of the ceaseless human quest for innovation, has become an integral part of our lives. It has not only revolutionized communication and information dissemination but also transformed the way we live, work, and play.
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Another standout speech from this collection is the talk on the Google Glass, which is a much more accurate reflection of the sophistication of modern technology. From health-related products to robotic evolution and new smartphones, this collection offers feelings of nostalgia when stacked up against the new products being unveiled at CES 2014.
Speech on Importance Of Technology
1-minute Speech on Importance Of Technology. Ladies and Gentlemen, Technology is like the magic wand of our times. It's not just about shiny new phones or fast cars. It is a tool that is making our lives easier, better, and a lot more exciting. Think about a day in your life. You wake up to the sound of an alarm, that's technology.
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10. Steve Jobs, Stanford (2005) "Our time is limited, so don't waste it living someone else's life. Don't be trapped by dogma — which is living with the results of other people's thinking. Don't ...
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Technology's far-reaching impact touches just about everything in society, and informative speeches about technology can help audiences understand that influence. Speakers can rely on government research, data and studies as well as articles that appear in newspapers, magazines and in the broadcast media to inform their speech.
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Read short & Long speeches on Technology, 1 minute, 2 & 3 minutes speeches on technology, advantages, disadvantages of technology for student. Skip to primary navigation; ... The modern technology is the most, essential and powerful tool of development. It is dual edged sword with both blessing, boon and bane, advantages and disadvantages, pros ...
2 Minute Speech On The Modern Technology In English
The technologies created throughout the 20th century have historically been referred to as modern technology. It has been used for transportation, recreation, communication, and many more purposes. Technology has become a need and a significant aspect of our life in the current day. It helps us live more comfortably and easily since we rely on it.
IELTS Speaking Part 3: Technology
Topic: Technology. 1. Describe the advantages and disadvantages of modern technology. Answer: Modern technology today is an integral part of our lives, and therefore, we will have to live with it whether we like it or not. Among the advantages of modern technology, I can say that it has made our lives much easier than it used to be ever before ...
Speech Technology Progress Based on New Machine Learning Paradigm
Modern speech technology systems rely on interdisciplinary research in the areas of multimodal signal processing and artificial intelligence, and a number of methods and algorithms have been developed with the aim of solving various problems: dialogue systems based on speech recognition and synthesis, including emotional speech, speaker ...
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Technology refers to machines, devices and scientific knowledge that makes life easier for us. In recent times, humankind has seen unprecedented scientific progress. As a result, technology has taken over every aspect of our lives. From cars to mobile phones to television sets, we see technology all around us. It is an indispensable part of our ...
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Download BibTex. The task of speech recognition is to convert speech into a sequence of words by a computer program. As the most natural communication modality for humans, the ultimate dream of speech recognition is to enable people to communicate more naturally and effectively. While the long-term objective requires deep integration with many ...
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Columbia University took steps to ensure Jewish and Israeli students felt safe on campus while ensuring pro-Palestinian demonstrators had a place to exercise their free speech rights, university president Minouche Shafik will tell the congressional committee that hammered other Ivy League presidents.. The big picture: Harvard president Claudine Gay and University of Pennsylvania's Liz Magill ...
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Tesla started selling its Cybertruck - an unconventional stainless steel pickup and the company's first new car in almost four years - in December. The vehicle costs at least $79,900 (£64,300 ...

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