Mongolian large vocabulary continuous speech recognition method

Abstract

The invention discloses a Mongolian large vocabulary continuous speech recognition method. The method is composed of a preprocessing phase, a preparation phase, a training phase, a decoding phase and a synthesis conversion phase. In the preprocessing phase, text training data is segmented and a pronunciation dictionary is established; in the preparation phase, acoustic features are extracted from input voice signals; in the training phase, an acoustic model is trained by use of a whole-word pronunciation dictionary, and a language model is trained by use of a training text after segmentation; in the decoding phase, by use of the acoustic model, the language model and the pronunciation dictionary, the input acoustic features are recognized into text information; and in the synthesis conversion phase, case suffix errors in a decoding process are corrected by use of rules, stems are merged with case suffixes, and finally, sentences composed of Mongolian words are output. According to the invention, the problems of too long voice recognition time and language model data sparsity in a voice recognition system because the voice recognition system cannot include large-scale Mongolian words and the vocabulary is too large in the prior art are solved.

Description

technical field [0001] The invention belongs to the technical field of speech recognition and relates to a method for continuous speech recognition of Mongolian large vocabulary. Background technique [0002] Speech recognition is a key technology to realize human-machine voice communication. It involves multiple disciplines such as acoustics, linguistics, digital signal processing, and computer science. It is a cutting-edge technology in the field of information processing. The main problem to be solved is how to Received voice messages are converted to text messages. According to different task requirements, speech recognition can be divided into several types: speaker recognition, keyword detection and continuous speech recognition. At present, it has been successfully applied to various fields such as industry, home appliances, communications, automotive electronics, medical care, home services and consumer electronics, and has achieved very good results. [0003] The ...

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Problems solved by technology

[0009] In order to achieve the above object, the present invention provides a method for continuous speech recognition of large Mongolian vocabulary, which solves the problem that the speech recognition system in the prior art cannot contain large-scale Mongolian words, and the time of speech recognition is too long caused by the excessive amount of words , the problem of sparse language model data in speech recognition systems

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