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Communicate with the machine and let the machine understand what you are saying. This is what people have long dreamed of. The image of the China Internet of Things School and Enterprise Alliance has to use the speech recognition ratio as the "machine's auditory system." Speech recognition technology is a high-tech technique that allows a machine to transform a speech signal into a corresponding text or command through a recognition and understanding process. Speech recognition technology mainly includes three aspects: feature extraction technology, pattern matching criterion and model training technology. The voice recognition technology car network has also been fully quoted. For example, in the wing truck network, you can set the destination direct navigation by pressing the one-touch customer service dictation, which is safe and convenient.
Speech recognition is an interdisciplinary subject. In the past two decades, speech recognition technology has made significant progress and has begun to move from the laboratory to the market. It is expected that in the next 10 years, speech recognition technology will enter various fields such as industry, home appliances, communications, automotive electronics, medical care, home services, and consumer electronics. The application of speech recognition dictation machines in some fields has been rated by the US press as one of the ten major events in computer development in 1997. Many experts believe that speech recognition technology is one of the ten most important technological development technologies in the field of information technology between 2000 and 2010. The areas covered by speech recognition technology include: signal processing, pattern recognition, probability theory and information theory, vocal mechanism and auditory mechanism, artificial intelligence, and so on.
According to the different objects identified, the speech recognition tasks can be roughly divided into three categories, namely, isolated word recogniTIon, keyword recognition (or keyword detection, keyword spotTIng) and continuous speech recognition. Among them, the task of isolated word recognition is to identify previously known isolated words, such as "boot", "shutdown", etc.; continuous speech recognition task is to identify any continuous speech, such as a sentence or a paragraph; continuous voice stream The keyword detection is for continuous speech, but it does not recognize all the words, but only detects where several known keywords appear, such as detecting the words "computer" and "world" in a paragraph. .
According to the targeted speaker, the speech recognition technology can be divided into specific person speech recognition and non-specific person speech recognition. The former can only recognize the voice of one or several people, while the latter can be used by anyone. Obviously, the non-specific person speech recognition system is more suitable for practical needs, but it is much more difficult than the identification for specific people.
In addition, according to voice devices and channels, it can be divided into desktop (PC) speech recognition, telephone speech recognition, and embedded device (mobile phone, PDA, etc.) speech recognition. Different acquisition channels can distort the acoustic characteristics of human pronunciation, so it is necessary to construct their own recognition systems.
The application fields of speech recognition are very wide. Common application systems include: voice input system, which is more natural and more efficient than the keyboard input method. The voice control system uses voice to control the device. Operation is faster and more convenient than manual control. It can be used in many fields such as industrial control, voice dialing system, smart home appliances, voice-activated intelligent toys, etc. Intelligent dialogue inquiry system, operating according to customer's voice, providing users with natural Friendly database retrieval services, such as family services, hotel services, travel agency services, booking systems, medical services, banking services, stock inquiry services, etc.
The system is essentially a pattern recognition system, including three basic units: 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 the microphone and then added to the input end of the recognition system. First, the pre-processing is performed, then the speech model is established according to the characteristics of the human voice, the input speech signal is analyzed, and the required features are extracted. Create a template for speech recognition. In the process of recognition, the computer compares the voice template stored in the computer with the characteristics of the input voice signal according to the model of speech recognition, and finds a series of optimal matching with the input voice according to a certain search and matching strategy. template. Then according to the definition of this template, the recognition result of the computer can be given by looking up the table. Obviously, this optimal result has a direct relationship with the choice of features, the quality of the speech model, and the accuracy of the template.