Voice communication with the machine, let the machine understand what you say, this is what people have long dreamed of. The image of the China Internet of Things School-Enterprise Alliance must compare speech recognition as a "machine's auditory system." Speech recognition technology is a high technology that allows machines to transform speech signals into corresponding text or commands through recognition and understanding. Speech recognition technology mainly includes three aspects: feature extraction technology, pattern matching criterion and model training technology. Voice recognition technology has also been fully cited in the Internet of Vehicles. For example, in the Wing Truck Networking, simply press the push-to-talk customer service staff to dictate the destination direct navigation, safe and convenient.
Speech recognition is an interdisciplinary subject. In the past two decades, speech recognition technology has made significant progress and started to move from the laboratory to the market. It is expected that in the next 10 years, voice recognition technology will enter various fields such as industry, home appliances, communications, automotive electronics, medical care, home services, consumer electronics, and so on. The application of speech recognition dictation machine in some fields was rated as one of the ten major events of computer development in 1997 by the US press. Many experts believe that speech recognition technology is one of the ten most important technological development technologies in the field of information technology from 2000 to 2010. The fields involved in speech recognition technology include: signal processing, pattern recognition, probability theory and information theory, vocalization mechanism and auditory mechanism, artificial intelligence and so on.
According to different recognition objects, speech recognition tasks can be roughly divided into three categories, namely isolated word recognition (isolated word recogniTIon), keyword recognition (or keyword spotTIng) and continuous speech recognition. Among them, the task of isolated word recognition is to recognize the isolated words known in advance, such as "power on", "off", etc .; the task of continuous speech recognition is to recognize any continuous speech, such as a sentence or a paragraph; continuous speech flow The keyword detection in is aimed at continuous speech, but it does not recognize all the text, but only detects where certain known keywords appear, such as detecting the two 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 speech of one or a few people, while the latter can be used by anyone. Obviously, the non-specific person speech recognition system is more in line with actual needs, but it is much more difficult than the specific person recognition.
In addition, according to the voice device and channel, it can be divided into desktop (PC) voice recognition, phone voice recognition and embedded device (mobile phone, PDA, etc.) voice recognition. Different acquisition channels will distort the acoustic characteristics of human pronunciation, so it is necessary to construct their own recognition systems.
Voice recognition has a wide range of application fields. Common application systems include: voice input system, which is more in line with people's daily habits, more natural and more efficient than keyboard input method; voice control system, which uses voice to control the device Operation is faster and more convenient than manual control, and can be used in many fields such as industrial control, voice dialing system, smart home appliances, voice-activated smart toys, etc .; the intelligent dialogue query system operates according to the customer's voice, providing users , Friendly database search services, such as home services, hotel services, travel agency service systems, ticket booking systems, medical services, banking services, stock query services, etc.
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.
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