What does voice recognition mean?
Voice recognition (speech recognition or SRT) is an intrinsic technique in computing technology by which particular software and machines can be produced to identify, distinguish and authenticate the voice properly. Regarding this fact, recording devices can capture most phrases and words. Then this data needs to be transferred from analog form to digital formats.
Voice recognition assesses the voice biometrics related to human characteristics, such as the frequency and flow of the voice and the natural accent.
A brief history of speech recognition
Calculation power of computers and artificial intelligence are two incredibly powerful tools in order to make some changes in this space. With massive amounts of speech data combined with faster processing power, voice recognition has hit an inflection point where its potentials and capabilities are very close to humans. But where did this long journey start from?
The first speech recognition systems could merely distinguish English numbers and not words. Bell Laboratories created the “Audrey” system which could recognize an individual voice speaking digits aloud In 1952. After that, the biggest name of that time, IBM started to invest massively in the Shoebox project. By the year 2001, speech recognition systems had managed to achieve approximately 80% accuracy. At the time when Google launched Google Voice, lots of people were able to use new technologies.
It was a significant achievement for Google as well since they could collect data from billions of searches. In 2011, Apple launched its own audio assistant named “Siri” which was similar to Google’s Voice Search. Since then, and with Amazon’s Alexa, we have witnessed that consumers becoming more and more interested in machines.
How does speech recognition work?
There are a lot of baffling factors involved in the overall speech recognition process. However, for easier comprehension, we are going to jot down the complex technical steps of speech recognition processes.
First thing first, let’s look at how a voice could be created. When you start to speak, you create vibrations in the air molecules. If we can capture and understand these signals, we will be able to process them. The analog-to-digital converter (ADC) translates analog waves into digital data that computers can understand and process. This device converts the human’s voice through complex mathematical functions and precise measurements into digital signals.
Meanwhile, we need to remove unwanted noise from the digital version, because a microphone captures other voices exist in the environment.
We all know that people don’t always speak at the same speed and intonation. So in order to match the input (voice) and samples already stored in the database, we need to adjust the speed and frequency level. Then it is time to separate signals into a few hundredths of second segments or different frequency intervals.
After this, a program matches these segments with predefined phonemes (A phoneme is the smallest element of a language) in order to distinguish meaningful expressions. The number of phonemes is not the same in different languages; For example, we have 40 phonemes in the English language. Afterward, the software examines phonemes in the context of those used around it. A complex statistical model is used to compare these phonemes using a large library of known words, phrases, and sentences. This allows the program to determine what the speaker is probably trying to say. Finally, it can transmit the output to the computer in order to operate a command.
What is speech recognition used for?
The accuracy and reliability of speech recognition systems have improved a lot in the last couple of years. So, it seems rational that forward-thinking companies are now adapting to this technology in order to enhance their operation quality. Here are the popular uses of voice recognition technology.
- voice search
voice search can make the machine and human interaction faster and easier more than ever. Maybe the best part of this voice recognition is that you do not have to wait for the browser to interpret your words. This would be the best alternative for a person who suffers from some kinds of disability and can not type on the screen or use a keyboard.
- virtual assistant
A virtual (personal) assistant is a cloud-based device that takes users command and tries to complete tasks online using the internet and AI. These tasks include answering phone calls, managing their appointments, controlling your lights, door locks, appliances and much more. The most well-known leaders in the market are Google Assistant, Amazon Alexa, Siri (from Apple), and Microsoft’s Cortana.
- automated identification
Identity fraud is now one of the most concerning problems many countries have been trying to solve it. This is where some advanced speech recognition systems can play a key role. we can use voice biometrics in order to authorize people. Fraud prevention services are now using this technology as the main method in combating telephone-based crime.
As we mentioned, speech recognition technology has a lot of utilization. For instance, companies authentication or identification. No matter whether you feel comfortable using them or no, they will become increasingly crucial. Enabling voice-driven commands for mobile applications has provided customers more self-certification opportunities. As represented in the Visa® survey, it will be as effective as a tool for customer satisfaction, retention, and acquisition as it will be for cost reduction and fraud prevention.