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Method and system of speech recognition based on matching model secondary identification

A speech recognition and secondary recognition technology, applied in speech recognition, speech analysis, instruments, etc., can solve the problems of speech recognition accuracy drop and affect human-computer interaction experience, so as to ensure accuracy, improve user experience, and recognize accurately high degree of effect

Inactive Publication Date: 2017-09-08
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

[0004] However, the method of improving the accuracy of the speech recognition system by adjusting the model structure and parameters will lead to a sharp drop in speech recognition accuracy when the actual user speech noise background does not match, seriously affecting the human-computer interaction experience

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  • Method and system of speech recognition based on matching model secondary identification

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Embodiment Construction

[0027] Such as figure 1 As shown, the present invention is based on the speech recognition method of matching model secondary recognition, comprises the following steps:

[0028] (10) Speech processing: perform preprocessing and feature extraction on the speech input by the user;

[0029] In the prior art, a common speech recognition model modeling process includes the following steps:

[0030] (1) Obtain a sufficient amount of labeled training data, extract the Mel domain cepstral coefficient (MFCC) of each training sample as the acoustic feature; sort out the labeled information of the training data to extract the text feature vector

[0031] (2) Input the acoustic feature vectors of the training samples into the deep neural network (DNN) composed of restricted Boltzmann machine (RBM) stacks, and use the GMM-HMM baseline system to obtain the output layer of the neural network through forced alignment. The error signal of the output layer is obtained by comparing the networ...

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Abstract

The present invention discloses a method and system of speech recognition based on matching model secondary identification. The method comprises the following steps: (10) speech processing: performing preprocessing and feature extraction of speed input by users; (20) speech identification: identifying and analyzing users' speed information, and extracting and storing users' gender and environment noise information; (30) user evaluation: receiving users' feedback information about a first identification result, if the first identification result is not accorded with an expectation, going on performing secondary identification, and emitting a secondary identification request; and (40) matching model identification: matching an optimal speed identification model according to the users' gender and environment noise information under the secondary identification request, and performing reidentification and output of an analysis result. The method and system of speech recognition based on matching model secondary identification are high in identification accuracy and good in user experience.

Description

technical field [0001] The invention belongs to the technical field of human-machine voice interaction, in particular to a voice recognition method based on secondary recognition of a matching model with high recognition accuracy and good user experience and a system for realizing the method. Background technique [0002] Speech recognition is an ideal intermediary tool for human-computer interaction and an important technology to promote the development of machines to be more intelligent. An intelligent machine that can understand human speech, think and understand human intentions, and finally respond to human voice or action has always been one of the ultimate goals of artificial intelligence. [0003] In the context of big data, machine learning has gradually penetrated into fields such as smart home, vehicle voice, and identification. The deep learning research method based on big data is of great significance to the improvement of the performance of the speech recogni...

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Application Information

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IPC IPC(8): G10L15/22G10L15/20G10L15/14G10L15/08G10L15/06G10L25/30G10L17/26
CPCG10L15/063G10L15/083G10L15/14G10L15/20G10L15/22G10L17/26G10L25/30G10L2015/0631
Inventor 赵兆何云亚许志勇
Owner NANJING UNIV OF SCI & TECH
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