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What Is The Future Of Voice Recognition Technology

20 August, 2020 12 min read

What Is The Future of Voice Recognition Technology

What is the scope of Voice Recognition Technology?

 

Play this, play that, you must have often listened to people commanding Alexa. Isn’t it fascinating? Have you ever wondered which technology is used in it? It uses Voice Recognition Technology.

The demand for voice recognition devices is rapidly growing as we are becoming more inclined towards technology. Reportedly, Google sold tens of millions of Echo devices in 2020 and became one of the top-notch voice selling devices to date.

 

What is Voice Recognition Technology?

A machine program works on the spoken commands and acts accordingly, this ability is called Voice Recognition Technology. With the surge in AI technology, Voice Recognition has gained dynamic momentum. With the popularity of Amazon’s Alexa and Apple’s Siri, there is a tremendous shift towards this technology. 

Voice recognition encourages customers to interact with technology by speaking to it. They can be asked to set reminders and do simple tasks.  

 

Amazon’s Alexa vs Apple’s Siri?  

 

Digital voice assistants such as Alexa and Siri are used by a multitude of people across the globe. Through AI, these assistants gather your data in real-time and offer the desired output.

 

When you speak to Alexa, your recorded request is sent to Amazon’s cloud to process it and afterward, Alexa responds. Like when you say, “Alexa, play the Hits of 90 from the Amazon Music library,” it processes the recording of your request then plays the desired hits from its music library.

 

However, Siri processes the information from your phone to generate output. Whatever you say to Siri, the request is sent to Apple’s cloud to generate output. 

In Amazon, there are Echo devices that are created to store data and these devices possess microphones that process data on the cloud and hence, it gets encrypted.

 

Whereas in the case of Siri, it collects data like names of your mobile contacts, music, books, names of your photo albums, etc.

 

In the case of Alexa, if you want to delete voice history, you just need to say,” Alexa, delete whatever I said today.”

 

But in Siri, on your iPhone, go to Siri, then in Siri, open Dictation History, then Delete Dictation History. 

 

So, the process takes time if compared with Alexa. 

 

How does voice recognition work?

 

Voice recognition software converts analog audio into digital signals, which is known as analog-to-digital conversion. A computer understands the signal when it has a digital database, consisting of vocabulary and a large number of words & syllables. For comparing data to signals, it should have a nice speed because when a program runs, the speech patterns are put into the hard drive and loaded into memory. Then, a comparator compares the stored patterns with the output of the A/D converter, which is called pattern recognition.

 

The Voice recognition program’s vocabulary size has a relation with the RAM’s capacity of the computer. The speed of the voice recognition system is quite fast if the entire vocabulary is loaded into RAM. 

 

Today, voice technology will continue its upward journey in terms of both popularity and adoption. It started from being a part of science fiction, and now it is a valuable asset that is showing no sign of deceleration anytime soon. With the seamless blend of AI and voice assistance, we are witnessing a surge in voice-based solutions to the complex problems of customers. This has also set a stage for the upcoming businesses to innovate and drive the advancements in this field. Rannkly has curated a few trends and upcoming features which might be visible in the near future. 

 

More focus on any-accent language models

 

In order to cater to the huge diversity, most Automated Speech Recognition providers have multiple accent packs for their languages. It is expected that these ASR providers will shift towards the concept of one model per language as accents continue to transform and develop further. Brands will be confronted with challenges pertaining to what their product offers to the global audience, in addition to balancing the cost of deploying and operating language packs. As global accents will take center-stage with the wider adoption of voice technology, organizations and ASR firms will have to figure out the best strategy to deliver voice recognition in the global application in an efficient manner.

 

Personalized Experiences

 

Voice assistants will evolve further to provide more personalized experiences as they continue to learn and differentiate between different voices. For example, Google Home has the feature to add up to six users and detect their voices. This provides a lot of scope for customizations to its users. Someone might ask for their To-Do List or What is my schedule today? And the assistant would provide information for individual users. Features, like Learn my voice, will also allow users to create different speech profiles so that the technology can detect who is giving the command for more customized experiences.

Instagram is also reportedly working on a new feature that will help users keep track of what is being said on a video on its own. This voice note feature is quite similar to how YouTube's live caption works and will be helpful when the accent or audio is not very understandable.

Change in search behavior

Voice search has been trending for a couple of years and there is one thing that is absent from voice assistants is the visual interface. Users cannot see or touch a voice interface if it is not connected to a third-party app because of which search behaviors will witness major changes. On the basis of research analysis by ComScore, it was estimated that 50% of all searches will be via voice technology by the end of 2020.

Voice search technology is all set to change the way brands interact with customers. In a recent bid, Facebook has also announced it will pay select users who agree to record their voice to improve its speech recognition technology. The social media giant also intends to pay select users to record snippets of audio through a new program called Pronunciations.



 

Spoken Language Translation

 

Innovation within voice means that the industry will continue to evolve with an expectation that speech recognition accuracy will improve, and features and intelligence will also grow around it.

Imagine in a country like India, where users tend to switch between two languages, the ability to automatically identify a spoken language and enabling transcription could humanize voice tech even more. This optimizes the accuracy of a specific media file or when transcribing in real-time. Transcription and translation features have the potential to add significant value if used together. Audio can be transcribed in one language, translated word for word, and then fed into a text-to-speech engine. To reflect a natural output, additional understanding will be required to enable the delivery of a transcribed, translated and machine has spoken output that is almost indistinguishable from a natural speaker. 

Voice recognition uses

 

Voice Recognition Technology has a multitude of uses and its need has magnified because of growing AI and consumer’s acceptance.

It has myriad uses starting from setting reminders, browsing the internet, playing music, sharing weather information, responding to questions and requests. 

The government is also planning to use Voice Recognition Technology for security purposes. 

 

Voice recognition advantages and disadvantages

 

Voice recognition helps to do a multitude of tasks when you directly give commands speaking to Alexa, Siri, etc. With the help of machine learning and algorithms, voice recognition quickly responds to act on your spoken words and convert them into written words. 

However, there are few drawbacks associated with this technology. There can be a background noise that can be minimized by using the system in a quiet environment. Some words have the same pronunciation but different meanings, which can create confusion. This problem can be solved by using stored contextual information. For this, there is a requirement for faster processors and more RAM.

 

Voice recognition is the ultimate reality, so try it out by yourself to see its wonders in the technologically driven world. You just need to wait and watch. This technology will bring a dynamic revolution in the lives of humans. 

 

What is the scope of Voice Recognition Technology?

 

Play this, play that, you must have often listened to people commanding Alexa. Isn’t it fascinating? Have you ever wondered which technology is used in it? It uses Voice Recognition Technology.

The demand for voice recognition devices is rapidly growing as we are becoming more inclined towards technology. Reportedly, Google sold tens of millions of Echo devices in 2020 and became one of the top-notch voice selling devices to date.

 

What is Voice Recognition Technology?

 

A machine program works on the spoken commands and acts accordingly, this ability is called Voice Recognition Technology. With the surge in AI technology, Voice Recognition has gained dynamic momentum. With the popularity of Amazon’s Alexa and Apple’s Siri, there is a tremendous shift towards this technology. 

Voice recognition encourages customers to interact with the technology by speaking to it. They can be asked to set reminders and do simple tasks.  

 

Amazon’s Alexa vs Apple’s Siri?  

 

Digital voice assistants such as Alexa and Siri are used by a multitude of people across the globe. Through AI, these assistants gather your data in real-time and offer the desired output.

 

When you speak to Alexa, your recorded request is sent to Amazon’s cloud to process it and afterward, Alexa responds. Like when you say, “Alexa, play the Hits of 90 from the Amazon Music library,” it processes the recording of your request then plays the desired hits from its music library.

 

However, Siri processes the information from your phone to generate output. Whatever you say to Siri, the request is sent to Apple’s cloud to generate output. 

In Amazon, there are Echo devices that are created to store data and these devices possess microphones that process data on the cloud and hence, it gets encrypted.

 

Whereas in the case of Siri, it collects data like names of your mobile contacts, music, books, names of your photo albums, etc.

In the case of Alexa, if you want to delete voice history, you just need to say,” Alexa, delete whatever I said today.”

But in Siri, on your iPhone, go to Siri, then in Siri, open Dictation History, then Delete Dictation History. 

 

So, the process takes time if compared with Alexa. 

 

How does voice recognition work?

 

Voice recognition software converts analog audio into digital signals, which is known as analog-to-digital conversion. A computer understands the signal when it has a digital database, consisting of vocabulary and a large number of words & syllables. For comparing data to signals, it should have a nice speed because when a program runs, the speech patterns are put into the hard drive and loaded into memory. Then, a comparator compares the stored patterns with the output of the A/D converter, which is called pattern recognition.

 

The Voice recognition program’s vocabulary size has a relation with the RAM’s capacity of the computer. The speed of the voice recognition system is quite fast if the entire vocabulary is loaded into RAM. 

Today, voice technology will continue its upward journey in terms of both popularity and adoption. It started from being a part of science fiction, and now it is a valuable asset that is showing no sign of deceleration anytime soon. With the seamless blend of AI and voice assistance, we are witnessing a surge in voice-based solutions to the complex problems of customers. This has also set a stage for the upcoming businesses to innovate and drive the advancements in this field. Rannkly has curated a few trends and upcoming features which might be visible in the near future. 

 

More focus on any-accent language models

 

In order to cater to the huge diversity, most Automated Speech Recognition providers have multiple accent packs for their languages. It is expected that these ASR providers will shift towards the concept of one model per language as accents continue to transform and develop further. Brands will be confronted with challenges pertaining to what their product offers to the global audience, in addition to balancing the cost of deploying and operating language packs. As global accents will take center-stage with the wider adoption of voice technology, organizations and ASR firms will have to figure out the best strategy to deliver voice recognition in the global application in an efficient manner.

 

Personalized Experiences

 

Voice assistants will evolve further to provide more personalized experiences as they continue to learn and differentiate between different voices. For example, Google Home has the feature to add up to six users and detect their voices. This provides a lot of scope for customizations to its users. Someone might ask for their To-Do List or What is my schedule today? And the assistant would provide information for individual users. Features, like Learn my voice, will also allow users to create different speech profiles so that the technology can detect who is giving the command for more customized experiences.

Instagram is also reportedly working on a new feature that will help users keep track of what is being said on a video on its own. This voice note feature is quite similar to how YouTube's live caption works and will be helpful when the accent or audio is not very understandable.

Change in search behavior

Voice search has been trending for a couple of years and there is one thing that is absent from voice assistants is the visual interface. Users cannot see or touch a voice interface if it is not connected to a third-party app because of which search behaviors will witness major changes. On the basis of research analysis by ComScore, it was estimated that 50% of all searches will be via voice technology by the end of 2020.

Voice search technology is all set to change the way brands interact with customers. In a recent bid, Facebook has also announced it will pay select users who agree to record their voice to improve its speech recognition technology. The social media giant also intends to pay select users to record snippets of audio through a new program called Pronunciations.



 

Spoken Language Translation

 

Innovation within voice means that the industry will continue to evolve with an expectation that speech recognition accuracy will improve, and features and intelligence will also grow around it.

Imagine in a country like India, where users tend to switch between two languages, the ability to automatically identify a spoken language and enabling transcription could humanize voice tech even more. This optimizes the accuracy of a specific media file or when transcribing in real-time. Transcription and translation features have the potential to add significant value if used together. Audio can be transcribed in one language, translated word for word, and then fed into a text-to-speech engine. To reflect a natural output, additional understanding will be required to enable the delivery of a transcribed, translated and machine has spoken output that is almost indistinguishable from a natural speaker. 

Voice recognition uses

 

Voice Recognition Technology has a multitude of uses and its need has magnified because of growing AI and consumer’s acceptance.

It has myriad uses starting from setting reminders, browsing the internet, playing music, sharing weather information, responding to questions and requests. 

The government is also planning to use Voice Recognition Technology for security purposes. 

 

Voice recognition advantages and disadvantages

 

Voice recognition helps to do a multitude of tasks when you directly give commands speaking to Alexa, Siri, etc. With the help of machine learning and algorithms, voice recognition quickly responds to act on your spoken words and convert them into written words. 

 

However, there are few drawbacks associated with this technology. There can be a background noise that can be minimized by using the system in a quiet environment. Some words have the same pronunciation but different meanings, which can create confusion. This problem can be solved by using stored contextual information. For this, there is a requirement for faster processors and more RAM.

 

Voice recognition is the ultimate reality, so try it out by yourself to see its wonders in the technologically driven world. You just need to wait and watch. This technology will bring a dynamic revolution in the lives of humans. 

 

Vishnu Sharma

Vishnu Sharma

CEO at Coder Value Pvt. Ltd.

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