What Is Speech Recognition and Where Is It Used?

Currently, numerous technical means can perceive (recognize) spoken speech messages. These include computers, medical electronic equipment, cars, mobile phones, etc.

Definition of Speech Recognition

At first glance, everything seems very simple. A person utters a word (phrase), and the technical system adequately reacts to it. Either it executes the command contained in the word (phrase), or types the dictated text, or otherwise “disposes” of the information extracted from the phrase.

The rapid development of speech recognition using a personal computer began in 1993. There are two key tasks of speech recognition. The first is the achievement of 100% recognition on a limited set of commands for at least one speaker. The second is speaker-independent recognition of a continuous speech stream in real-time in an arbitrary language with acceptable quality. They are still not fully resolved, despite numerous attempts to solve these problems over the past 50 years.

Modern speech recognition systems already enable users to dictate words (phrases) in a common conversational manner. However, the process of continuous speech recognition, which gives up to 95% of the recognition quality under optimal conditions, still gives 5 errors per 100 characters.

Let’s consider a sequence of actions for computer recognition of a speech signal that has become traditional. Typically, a speech recognition system consists of two models: acoustic and linguistic. The computer records the sound of speech as a digital signal and divides it into audio fragments several milliseconds in length. The acoustic model is responsible for converting the speech signal into a set of features that display information about the content of the speech message. The program performs sophisticated speech analysis by comparing audio fragments with speech samples recorded in memory.

The linguistic model analyzes the information received from the acoustic model and forms the final recognition result. Based on a probabilistic calculation, the computer determines exactly what the user might have said. The model is based on the concept of a phoneme – the smallest acoustic unit of a language. During the learning process, the computer recognizes the most important signs of the user’s pronunciation of phonemes and records the data obtained in the form of a user profile. During dictation, the user maintains the melody of speech and pronunciation as much as possible.

Possibilities of Modern Speech Recognition Technologies

The increase in the computing power of mobile devices made it possible to create programs for them with a speech recognition function. Among such programs, it is worth noting the Microsoft Voice Command application, which allows you to work with many applications using your voice. Another interesting program is Speereo Voice Translator, a voice translator. SVT is capable of recognizing phrases spoken in English and “speaking” in response in one of the selected languages.

Intelligent speech solutions that automatically synthesize and recognize a speech signal are the next step in the development of interactive voice systems (IVR). The use of an interactive phone application is not a trend at the moment but a vital necessity. Reducing the burden on contact center operators and secretaries, reducing labor costs, and increasing the productivity of service systems are just some of the benefits that prove the feasibility of such solutions.

Thus, automatic speech recognition and speech synthesis systems are increasingly used in telephone interactive applications. At the same time, the recognition systems are independent of the speakers; that is, they recognize the voice of any person.

The development of the so-called Silent Speech Interfaces (SSI) can be considered the next step in speech recognition technology. These speech processing systems rely on the acquisition and processing of speech signals at an early stage of articulation.

There are many commercial speech recognition systems currently on the market:

• Voice Type Dictation, Voice Pilot and ViaVoice from IBM;
• Dragon Dictate and Naturally Speaking from Nuance Communications;
• Voice Assist from Creative Technology;
• Listen for Windows from Verbex and many others.

Some of them (for example, ViaVoice and Naturally Speaking) are capable of introducing continuous speech. Nuance Communications, in particular, is constantly updating its Dragon NaturallySpeaking software, which allows dictating text documents, as well as controlling the computer using voice commands. It should be noted that this recognition tool works quite well only with spoken English.

Areas of Application of Speech Recognition Technologies

Let’s designate the main areas of application of speech recognition systems.

Automated User Interface

Today, for many people, communication with a computer is still difficult. Speech recognition systems can overcome these difficulties. The huge advantage of voice recognition systems is that they are much faster than any other type of interface. Voicemail software allows you to turn on your computer, dictate and send messages without touching your mouse and keyboard. 

Also, people with disabilities can get a more efficient way to interact with the computer.

The most obvious use of a continuous speech recognition system is to create automatic stenography systems. They can replace secretaries when dictating by voice the texts of letters, notes in a diary, and reports. In this case, there are not only savings by reducing the work of an expert but also an increase in the degree of confidentiality of information.

Mobile Device Management

It is known how inconvenient and dangerous it is to use mobile phones with the usual (tactile) dialing method while driving. Many countries have enacted laws prohibiting the use of such phones by drivers to reduce the number of accidents. Therefore, recently, mobile phones with voice dialing have become popular. They eliminate the need for a user to dial the desired number manually. It is enough to say the name of the person, and the connection will be made automatically. Audio monitoring and control systems are already in use in some car manufacturers. The car owner gives voice commands to control the temperature regime, radio, navigation system, which perceive the voice and execute commands (DIVO and VoiceCommander).

Information Services

Modern speech recognition systems are used, for example, for booking air tickets, viewing news, and accessing databases. Voice recognition technology quickly changed the telephone service market. Systems that recognize spoken speech operate in information call centers (IVR systems – Interactive Voice Response). These systems automate customer dialogue, eliminating the need for a huge number of operators to take phone calls and reducing staff costs. In addition, the quality of customer service is improved, since the connection to the machine is carried out almost immediately.

Business and Professional Support

For many years now, voice recorder systems designed for certain professions, such as doctors and lawyers, have been found in the software market. Many of these professions use speech recognition systems in their daily work. Voice-activated home appliances and gadgets have become popular.

Combined Human-Machine Interfaces

Over the past decade, the scope of such systems has expanded significantly and will continue to expand. They are used, in particular, to control limited access to an object using face and speech recognition. They are also used to perform financial transactions using speech and touch screens of ATMs.

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• Creation of readable transcripts;
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Conclusion 

So, modern speech recognition technologies can work with a continuous stream of speech and with unknown speakers. They understand the meanings of speech fragments of a limited vocabulary and take responsive actions. The systems operate in real-time and are capable of performing five functions:

1. Speech recognition – converting speech into a text consisting of separate words;
2. Understanding – grammatical analysis of sentences and recognition of semantic meaning;
3. Information recovery – obtaining data from operational sources based on the received semantic meaning;
4. Generation of linguistic information – the construction of sentences representing the received data in the language selected by the user;
5. Speech synthesis – the transformation of sentences into computer-synthesized speech.

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