Unsupervised classification and supervised correction fusion speech separation method related to spatial structural features

A space-structured and speech-separation technology, applied in speech analysis, speech recognition, instruments, etc., can solve the problems of insufficient generalization and accuracy of mixed-speech separation

Pending Publication Date: 2020-12-25
QINGDAO UNIV OF SCI & TECH +1
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Single-channel speech separation techniques include spectral subtraction, Wiener filtering, spectral estimation methods based on minimum mean square er

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  • Unsupervised classification and supervised correction fusion speech separation method related to spatial structural features
  • Unsupervised classification and supervised correction fusion speech separation method related to spatial structural features
  • Unsupervised classification and supervised correction fusion speech separation method related to spatial structural features

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[0057] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can also be implemented in other ways than those described here. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0058] Such as figure 1 As shown, this embodiment proposes a speech separation method of unsupervised classification and supervised correction fusion related to spatial structural features, including the following steps:

[0059] Step 1, extracting speech segment features based on time-delay cellular neural network;

[0060] Step 2, self-adaptive classification of speech segments based on dynamic growth self-organizing map neural ...

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Abstract

The invention discloses an unsupervised classification and supervised correction fusion speech separation method related to spatial structural features. The method comprises the steps of performing speech segment feature extraction based on a time-delay cellular neural network and speech segment unsupervised adaptive classification based on a dynamic growth self-organizing mapping neural network;adaptively correcting a speech separation model based on a particle swarm optimization algorithm, and reconstructing speech based on binary masking. According to the method, unsupervised classification and supervised correction are combined, the generalization and accuracy of separation of mixed voices with unknown speaker number are improved, and a theoretically supported and practically feasiblescheme is provided for the urgent practical problem of single-channel multi-speaker voice separation.

Description

technical field [0001] The invention relates to the field of speech signal processing, in particular to a speech separation method for fusion of unsupervised classification and supervised correction related to spatial structural features. Background technique [0002] In a complex acoustic environment, the speech signal of the target speaker is often disturbed by various noises, which seriously affects the recognition performance of the target speech. Speech separation technology can effectively remove noise interference in the actual environment, and provide more accurate and reliable information for subsequent speech signal processing. The application scenarios of speech separation technology are very extensive. For example, in the field of national defense and military affairs, in the background of war environment and conference monitoring, it is impossible to accurately analyze whether there is a specific speaker in the conference recording intercepted by the enemy simpl...

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Application Information

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IPC IPC(8): G10L21/0272G10L25/45G10L15/18G06N3/00
CPCG06N3/006G10L15/18G10L21/0272G10L25/45
Inventor 赵振刘扬焦美凤姜明顺张雷张法业杜泽厚
Owner QINGDAO UNIV OF SCI & TECH
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