Method, integrated with multiple types of end-to-end neural network structures, for cold symptoms of speaker

Abstract

The invention relates to a method, integrated with multiple types of end-to-end neural network structures, for cold symptoms of a speaker, and the method comprises the following steps: S1, constructing and training inputted voice, wherein a recognition network is an end-to-end neural network A of a convolution neural network and a long-short memory network; S2, constructing and training an inputted voice spectrum, wherein the recognition network is an end-to-end neural network B of the convolution neural network and the long-short memory network; S3, constructing and training the inputted voice spectrum, wherein the recognition network is an end-to-end neural network C of the convolution neural network and a full-connection network; S4, constructing and training the inputted voice MFCC features / CQCC features, wherein the recognition network is an end-to-end neural network D of the long-short memory network; S5, integrating the above four types of trained end-to-end neural networks, and carrying out the recognition of the cold symptoms of the speaker.

Description

technical field [0001] The present invention relates to the field of voiceprint recognition, and more specifically, relates to a speaker's cold symptom recognition method that integrates multiple end-to-end neural network structures. Background technique [0002] Speaker recognition, also known as voiceprint recognition, is a technology that uses pattern recognition technology to automatically identify speakers. The current speaker recognition technology has achieved good performance in experimental conditions, but in practice, the recognized speech will be affected by environmental noise and the speaker's health conditions, which reduces the robustness of the existing speaker recognition technology. Existing speaker recognition methods are mainly used to determine the speaker's identity, and there is no relevant recognition method applied to the speaker's cold symptoms at present. [0003] In the research of speech technology, researchers always hope to find the features t...

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a language that integrates multiple end-to-end neural network structures in order to solve the problems of feature extraction and pattern classification that are caused by the separation of feature extraction and pattern classification in the prior art. Human cold symptom recognition method, this method makes the entire speaker cold symptom recognition process simpler and faster by unifying feature learning and pattern classification, and has a wide range of application prospects

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