Voice recognition method and apparatus

A speech recognition and speech technology, applied in the computer field, can solve the problem of low discrimination in speech classification, and achieve the effect of improving sensitivity, discrimination and accuracy.
CN105895087AActive Publication Date: 2016-08-24HISENSE
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
HISENSE
Publication Date
2016-08-24

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Abstract

The embodiment of the invention, which relates to the technical field of the computer, provides a voice recognition method and apparatus, so that a problem of a low voice classification distinguishing degree during the voice classification process according to the existing voice recognition technology can be solved. The method comprises: at least two voice features of a to-be-recognized voice are extracted; on the basis of a multi-layer restricted Boltzmann machine (RBM), each of the at least two voice features is trained to obtain a depth voice feature corresponding to each voice feature; feature fusion is carried out on the depth voice feature corresponding to each voice feature, thereby obtaining a depth voice feature of the to-be-recognized voice; and the depth voice feature of the to-be-recognized voice is inputted into a classifier and is classified, so that a voice type of the to-be-recognized voice is obtained. The method and apparatus are applied to voice recognition.
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Description

technical field

[0001] The invention relates to the field of computer technology, in particular to a voice recognition method and device. Background technique

[0002] At present, with the continuous development of speech recognition technology in the field of human-computer interaction, in the process of human-computer interaction, having human-like emotional ability is a necessary basis for machine intelligence. In the prior art, when a computer performs speech emotion recognition or speech local accent recognition, it is usually based on the directly extracted speech feature parameters (such as short-term energy, formant and pitch frequency, etc., which can represent prosodic features and sound quality of the speaker's emotion). feature parameters) and a classifier obtained from a shallow structure algorithm (for example, a support vector machine (English: Support Vector Machine, SVM for short)) to classify the speech.

[0003] However, due to the relatively small amount...

Claims

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