Post-processing methods for speech recognition

Abstract

The invention provides a post-processing method for voice recognition. The method includes the steps of converting a first character string of a voice recognition result to obtain a second character string, performing word segmentation on the second character string according to a preset rule to obtain a post-word-segmentation third character string to be retrieved, retrieving the third character string in a first standard lexicon to obtain a retrieval result set corresponding to the third character string, determining the pronunciation similarity of the first character string according to a similar matrix, obtaining the matching degree of the second character string according to the retrieval result set and the pronunciation similarity, obtaining continuity and the length ratio of the second character string in the retrieval result set according to the second character string and the retrieval result set, obtaining a matching value of the first character string according to the continuity, the length ratio and the matching degree, and obtaining a matching result according to the matching value. According to the method, the voice recognition accuracy of a voice recognition technology in the prior art is improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of computers, and in particular, to a post-processing method for speech recognition. Background technique [0002] At present, the accuracy of speech recognition is relatively low in the environment of big data, especially big data with tens of millions of levels. Especially for the abbreviated terms, the recognition accuracy is lower. [0003] For this reason, in the prior art, speech recognition accuracy is improved by optimizing speech models, acoustic models, etc. of speech recognition. With the development of speech recognition technology, it is no longer possible to further improve the accuracy of speech recognition by optimizing the speech model and acoustic model of speech recognition. [0004] Therefore, how to improve the accuracy of speech recognition in the speech recognition technology has become a technical problem to be solved at present. Contents of the invention [0005]...

AI Technical Summary

Problems solved by technology

[0002] At present, the accuracy of speech recognition is relatively low in the environment of big data, especially big data of more than tens of millions

Especially for abbreviations, the recognition accuracy is lower

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