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Speech Enhancement Method Based on Non-negative Low Rank and Sparse Matrix Factorization

A technology of sparse matrix and low-rank matrix, which is applied in the field of speech enhancement based on the principle of non-negative low-rank and sparse matrix decomposition, can solve the problems of decomposition error and affect the quality of speech auditory, and achieve a strong effect of robustness

Inactive Publication Date: 2016-10-05
KEY LAB OF SCI & TECH ON AVIONICS INTEGRATION TECH
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Problems solved by technology

Negative magnitude spectrum not only causes decomposition errors, but also produces music noise that is uncomfortable for the human ear, thus affecting the quality of speech hearing

Method used

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  • Speech Enhancement Method Based on Non-negative Low Rank and Sparse Matrix Factorization

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Embodiment Construction

[0035] The present invention will now be further explained in conjunction with the drawings, see figure 1 , A speech enhancement method based on the principle of non-negative low rank and sparse matrix decomposition, including the following specific steps:

[0036] 1) Perform preprocessing 101 on the noisy speech signal y(t); preprocessing 101 includes signal smoothing and framing to facilitate subsequent processing. Signal smoothing refers to calculating the current value of the noisy speech signal by using the mean value of the nearest neighbor signal at point P of y(t) to smooth the amplitude waveform of the noisy speech signal. In the present invention, the value of P is 3, namely The window function used for framing is the Hamming window, with a window length of 200 points, and the number of overlapping points moved between frames each time is 80 points;

[0037] 2) Perform DFT (Discrete Fourier Transform) 102 on the noisy speech signal after framing to obtain the signal sp...

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Abstract

The invention discloses a speech enhancement method based on the principle of non-negative low rank and sparse matrix decomposition. In this method, the noisy speech signal is first smoothed, framed and discrete Fourier transformed to obtain the noisy speech spectrum; then the noisy speech amplitude spectrum of each frame is arranged as a column vector in chronological order to form a noisy speech time-frequency Matrix, by performing non-negative low-rank and sparse matrix decomposition on the noisy speech time-frequency matrix, a non-negative low-rank and sparse matrix is ​​obtained; using the sparse matrix and noisy speech phase reconstruction to enhance the speech spectrum, and finally through the inverse Fourier Transformation results in enhanced speech in time domain form. The invention has strong adaptability to noise, does not need endpoint detection and model training, has few parameters and is easy to adjust, has good performance in strong noise environment, and has good application prospect.

Description

Technical field [0001] The invention relates to the field of signal processing, and is suitable for noise suppression of noisy speech, in particular to a speech enhancement method based on the principle of non-negative low rank and sparse matrix decomposition. Background technique [0002] Voice signals are the most natural and effective means for humans to communicate information. As mankind enters the information age, it is urgent to use advanced voice processing technology to promote the intelligentization of human society. As early as 2000, Bill Gates put forward that "the next 10 years will be the era of voice." In recent years, as Apple, Google, Microsoft and other companies have successively launched intelligent voice services, the intelligent voice industry has become an emerging industry in the field of information technology, and user awareness and market scale are gradually expanding. In particular, Apple’s newly launched smartphones have voice assistant functions, a...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L21/0232G10L21/0272
Inventor 孙成立须明王希敏谢坚筱
Owner KEY LAB OF SCI & TECH ON AVIONICS INTEGRATION TECH
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