Speech enhancement method based on non-local mean filtering

A non-local mean, speech enhancement technology, applied in speech analysis, instruments, etc., can solve the problems of difficult to achieve accurate estimation, easy residual noise in the background, affecting hearing quality, etc., to reduce music noise, improve clarity, and avoid excessive dependence. Effect

Inactive Publication Date: 2014-08-06
XIDIAN UNIV
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Problems solved by technology

[0005] The above-mentioned traditional speech enhancement methods need to obtain accurate noise power spectrum and prior SNR, but in reality, it is difficult to accurately estimate the noise power spectrum and prior SNR, so the background is easy to remain after speech enhancement Noise, affecting hearing quality

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  • Speech enhancement method based on non-local mean filtering
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  • Speech enhancement method based on non-local mean filtering

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Embodiment Construction

[0031] refer to figure 1 , the present invention is based on the speech enhancement method of non-local mean filter, and its realization steps are as follows:

[0032] Step 1, input the noisy speech, and calculate the power spectrum of the noisy speech signal.

[0033] 1.1) For the input noisy speech y(i), divide the noisy speech into N frames with 256 speech points per frame, and overlap 128 points between frames to obtain the frame-divided signal y λ (i 1 ), and for y λ (i 1 ) plus Hamming window to get the windowed signal y λ (i 1 )':

[0034] the y λ (i 1 )'=y λ (i 1 )*ham(256);

[0035] Among them, i represents the time-domain signal discrete point sequence, i=1,2,...,m, m represents the total number of voice sequence numbers, λ represents the number of frame sequences, λ=1,2,...,N, i 1 Indicates the sequence number in the frame, i 1 =1,2,...,256, ham(256) means a Hamming window with a size of 256 points;

[0036] 1.2) For the windowed signal y λ (i 1 )' t...

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Abstract

The invention discloses a speech enhancement method based on non-local mean filtering. The problem of high generation rate of musical noise after speech enhancement in the prior art is mainly solved. The method is implemented by the following steps of (1) inputting speech with noise, and calculating a signal power spectrum of the speech with noise; (2) performing modified spectral subtraction preprocessing on the power spectrum of the speech with noise to obtain an estimated power spectrum of the speech with noise; (3) obtaining an estimated frequency spectrum according to the estimated power spectrum, and performing short-time inverse Fourier transform on the estimated frequency spectrum to obtain preprocessed speech; (4) performing non-local mean filtering on the preprocessed speech, and calculating a corrected value of the speech; and (5) replacing the original speech with noise by using the calculated corrected value. According to the method, similar points in a neighborhood of a point to be enhanced are subjected to weighted averaging based on a non-local principle, so that background noise can be suppressed, the clarity of the speech is maintained, and the quality of the speech is effectively improved; the method can be used for mobile communication.

Description

technical field [0001] The invention belongs to the technical field of speech processing, specifically based on non-local mean value filtering, using the weighted average of similar signal points in the signal neighborhood to reduce speech noise, and can be used in mobile communication. Background technique [0002] Speech is a unique function of human beings, and it is also the most important means of transmitting information to each other. Speech in real life is inevitably affected by the surrounding environment. Some strong background noises, such as mechanical noise, voices of other speakers, etc., will seriously affect the quality of the voice signal. In addition, the transmission system itself will also generate various noises, so the signal at the receiving end is a noisy speech signal. The main goal of speech enhancement is to extract pure speech signals from noisy speech as much as possible at the receiving end, reduce the listening fatigue of listeners, and impro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L21/0232
Inventor 钟桦焦李成周伟田小林王爽侯彪王桂婷马文萍尚荣华
Owner XIDIAN UNIV
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