Speech recognition technology, also known as AutomaTIc Speech RecogniTIon (ASR), whose goal is to convert vocabulary content in human speech into computer-readable input, such as keystrokes, binary codes, or character sequences. Unlike speaker recognition and speaker confirmation, the latter attempts to recognize or confirm the speaker who made the speech rather than the vocabulary content contained therein. The system is essentially a pattern recognition system, including three basic units such as feature extraction, pattern matching, and reference pattern library. Its basic structure is shown in the following figure: The unknown voice is converted into an electrical signal by a microphone and then added to the input of the recognition system. First, it is preprocessed, and then a voice model is established according to the characteristics of human voice, the input voice signal is analyzed, and the required features are extracted. Create the template required for speech recognition. In the recognition process, the computer should compare the characteristics of the voice template stored in the computer with the input voice signal according to the model of voice recognition, and according to a certain search and matching strategy, find a series of optimal matches with the input voice template. Then according to the definition of this template, the identification result of the computer can be given by looking up the table. Obviously, this optimal result is directly related to the choice of features, the quality of the speech model, and the accuracy of the template. The system can be classified according to restrictions on the input speech. If considering the relevance of the speaker and the recognition system, the recognition system can be divided into three categories: (1) specific person speech recognition system. Only consider the recognition of the voice of the person. (2) Non-specific person voice system. Recognized speech has nothing to do with people. Usually, a large number of different people's speech databases are used to learn the recognition system. (3) Multi-person identification system. Usually can recognize the voice of a group of people, or become a specific group of voice recognition system, the system only requires training of the voice of the group of people to be recognized. If you consider the way of speaking, you can also divide the recognition system into three categories: (1) Isolated word speech recognition system. The isolated word recognition system requires a pause after entering each word. (2) Conjunction speech recognition system. The connection word input system requires that each word be pronounced clearly, and some consonants begin to appear. (3) Continuous speech recognition system. Continuous voice input is a continuous fluent input of natural fluency, and a large number of legato and accent will appear. If considering the vocabulary size of the recognition system, the recognition system can also be divided into three categories: (1) small vocabulary speech recognition system. A speech recognition system that usually includes dozens of words. (2) Speech recognition system with medium vocabulary. The recognition system usually includes hundreds of words to thousands of words. (3) Large vocabulary speech recognition system. Speech recognition systems that usually include thousands to tens of thousands of words. As the computing power of computers and digital signal processors and the accuracy of recognition systems improve, the classification of recognition systems based on vocabulary size also continues to change. It is currently a medium vocabulary recognition system, and it may be a small vocabulary speech recognition system in the future. These different limitations also determine the difficulty of speech recognition systems. The applicable fields are roughly divided into five categories: Office or business system. Typical applications include: filling in data forms, database management and control, keyboard function enhancement, and so on. Manufacturing: In quality control, voice recognition systems can provide a "hands-free" and "eyes-free" inspection (component inspection) for the manufacturing process. Telecommunications: A very wide range of applications are feasible in dial-up telephone systems, including the automation of operator assistance services, international and domestic remote e-commerce, voice call distribution, voice dialing, and classified orders. Medical: The main application in this area is to generate and edit professional medical reports from sound. Others: Including games and toys controlled and operated by voice, voice recognition system to help the disabled, voice control of some non-critical functions in vehicle driving, such as vehicle traffic control system, audio system. 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Summary of domestic listed companies of speech recognition technology_Speech recognition technology status_Speech recognition principle and application
1. Introduction to speech recognition technology