Multi-language speech recognition method based on language type and speech content collaborative classification

Abstract

The invention discloses a multi-language speech recognition method based on language type and speech content collaborative classification. The method comprises the following steps: 1) establishing andtraining a language type and speech content collaborative classification acoustic model; wherein the acoustic model is fused with a language feature vector containing language related information, and model adaptive optimization can be performed on a phoneme classification layer of a specific language by utilizing the language feature vector in a multi-language recognition process; 2) inputting aspeech feature sequence to be recognized into the trained language type and speech content collaborative classification acoustic model, and outputting phoneme posteriori probability distribution corresponding to the feature sequence; the decoder generating a plurality of candidate word sequences and acoustic model scores corresponding to the candidate word sequences in combination with the sequence phoneme posteriori probability distribution of the features; and 3) combining the acoustic model scores and the language model scores of the candidate word sequences to serve as an overall score, and taking the candidate word sequence with the highest overall score as a recognition result of the voice content of the specific language.

Description

technical field [0001] The invention relates to the field of multilingual speech recognition, in particular to a multilingual speech recognition method based on cooperative classification of language types and speech content. Background technique [0002] At present, the automatic speech recognition technology is very mature. Under the technical research of some speech recognition institutions, the recognition accuracy of the automatic speech recognition system can reach 94.5%, which can be said to have reached the human auditory perception ability. But this excellent automatic speech recognition system is limited to a few widely used languages, such as English and French. There are more than 5,000 languages ​​spoken by people all over the world, but only 10 of these 5,000 languages ​​are widely used, they are: Chinese, English, Russian, Spanish, Hindi, Arabic , Portuguese, Bengali, German and Japanese. For other languages, due to the small number of users, it is difficult...

AI Technical Summary

Problems solved by technology

This method requires prior knowledge of language-related information in the model training and testing stages, requires a lot of manual annotation work, and the performance of speech content recognition is not high

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