Voice Recognition: About the Technology and Its Importance for Marketers

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Content
Technology in life
Development of voice recognition systems
Quality of voice recognition systems
Global market players
The Value of Voice Recognition in Marketing
Did you know that voice recognition technologies have been around for 50 years? Scientists have been solving this problem for half a century, and only in the last few decades have IT azerbaijan phone numbers companies joined in. The result of the last year of work has been a new level of recognition accuracy and the widespread use of the technology in everyday and professional life.


Technology in life
Every day we use search engines. We search for where to have lunch, how to get to the right place or try to find the meaning of an unknown term. Voice recognition technology, which is used, for example, by Google or Yandex.Navigator, helps us spend a minimum of time on searching. It is simple and convenient.

Source:
http://www.limebridge.com.au/cartoons/technology

In a professional environment, technology helps simplify work several times. For example, in medicine, a doctor's speech is converted into the text of a medical history and a prescription immediately at the appointment. This saves time on entering patient information into documents. A system built into a car's on-board computer responds to driver requests, for example, helps find the nearest gas station. For people with disabilities, it is important to implement systems in the software of household appliances to control them using voice.

Development of voice recognition systems
The idea of ​​speech recognition has always looked promising. But already at the stage of recognizing numbers and the simplest words, researchers encountered a problem. The essence of recognition was reduced to building an acoustic model, when speech was presented as a statistical model that was compared with ready-made templates. If the model matched the template, the system decided that the command or number was recognized. The growth of dictionaries that the system could recognize required an increase in the power of computing systems.

Graphs of computer performance growth and reduction of recognition error in English-language speech recognition systems
Sources: Herb Sutter. The Free Lunch Is Over: A Fundamental Turn Toward Concurrency in Software
https://minghsiehee.usc.edu/2017/04/the ... re-coming/



Today, recognition algorithms are supplemented by language models that describe the structure of the language, for example, a typical sequence of words. The system is trained on real speech material.

A new stage in the development of technology was the use of neural networks. The recognition system is designed in such a way that each new recognition affects the accuracy of recognition in the future. The system becomes trainable.

Quality of voice recognition systems
The state of affairs in the development of technology today is expressed by the goal: from speech recognition to understanding. For this purpose, the key indicator was chosen - the percentage of errors in recognition. It is worth saying that such an indicator is also used in the recognition of the speech of one person by another. We skip some words, taking into account other factors, such as context. This allows us to understand speech even without understanding the meaning of individual words. For a person, the recognition error rate is 5.1%.

Other challenges in training a speech recognition system to understand language include emotions, unexpected changes in the topic of conversation, the use of slang, and the individual characteristics of the speaker: speech rate, timbre, pronunciation of sounds.

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Global market players
Several global players in the voice recognition platform market are well known. These are Apple, Google, Microsoft, IBM. These companies have sufficient resources for research and an extensive base for training their own systems. For example, Google uses millions of search queries that users happily ask themselves for training. On the one hand, this increases the accuracy of recognition, but on the other, it imposes limitations: the system recognizes speech in 15-second segments and counts on a “broad-based question.” The recognition error of the Google system is 4.9%. For IBM, this figure is 5.5%, and for Microsoft, 6.3% at the end of 2016.

Voice search in Russia was recently launched by Yandex. Considering the number of users, we can expect that recognition accuracy will soon be high.

The platform for use in professional fields is being developed by the American company Nuance. Among the areas of application are: medicine, law, finance, journalism, construction, security, and the automotive industry.

In Russia, the Speech Technology Center is the largest manufacturer of professional voice recognition and speech synthesis tools. The company's solutions have been implemented in 67 countries. The main areas of work: voice biometrics - voice identification; self-service speech systems - IVR , used in call centers; speech synthesizers. In the USA, the Russian company operates under the SpeechPro brand and conducts research on English speech recognition.