Voice enhancement method by combining empirical mode decomposition with wavelet threshold denoising

A wavelet threshold denoising and empirical mode decomposition technology, applied in speech analysis, instruments, etc., can solve the problem of easy distortion of EMD speech signals, and achieve the effect of accurate demarcation point, wide adaptability, and reduction of distortion.

Active Publication Date: 2019-05-21
FUZHOU UNIVERSITY
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[0005] In view of this, the purpose of the present invention is to propose a voice enhancement method combining empirical mode decomposition

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  • Voice enhancement method by combining empirical mode decomposition with wavelet threshold denoising
  • Voice enhancement method by combining empirical mode decomposition with wavelet threshold denoising
  • Voice enhancement method by combining empirical mode decomposition with wavelet threshold denoising

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[0044] The present invention will be further described below in conjunction with the drawings and embodiments.

[0045] It should be pointed out that the following detailed descriptions are all exemplary and are intended to provide further descriptions of the application. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0046] It should be noted that the terms used here are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate There are features, steps, operations, devices, component...

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Abstract

The invention relates to a voice enhancement method by combining empirical mode decomposition with wavelet threshold denoising. The method comprises the steps that firstly, a voice signal is subjectedto empirical mode decomposition, the eigen mode functions containing false frequency components are removed according to a cross correlation coefficient of eigen mode functions and the voice signal,and then a self-correlation function of the rest eigen mode functions is calculated; according to the self-correlation function atlas, the demarcation point of the eigen mode function component leadedby noises and the eigen mode function component leaded by the voice signal is determined, then the eigen mode function leaded by the noises is subjected to wavelet threshold denoising, finally, the voice signal is reconstructed by the eigen mode function component leaded by the signal and the eigen mode function component leaded by the noises after wavelet threshold denoising, and the enhanced voice signal is obtained. Compared with a conventional empirical mode decomposition method, the method can effectively reduce distortion of the voice signal, the denoising performance is improved, and the voice signal of the high signal to noise ratio can be obtained.

Description

technical field [0001] The invention relates to the field of speech signal processing, in particular to a speech enhancement method combining empirical mode decomposition and wavelet threshold value denoising. Background technique [0002] As one of the important carriers of information, voice contains a lot of information. In real life, the application scenarios based on voice interaction are becoming more and more common. However, voice signals will inevitably be polluted by the environment or the noise of the equipment during the communication process. Therefore, it is necessary to The speech signal is enhanced to obtain a speech signal with a signal-to-noise ratio as high as possible, so as to ensure the normal operation of subsequent speech signal applications and other processing tasks. [0003] Empirical Mode Decomposition (EMD) is an adaptive signal time-frequency processing method that is very suitable for nonlinear and non-stationary signal processing proposed by H...

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Application Information

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IPC IPC(8): G10L21/0264
Inventor 吴海彬李恝叶锦华
Owner FUZHOU UNIVERSITY
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