Method for realizing background noise suppressing based on multiple statistics model and minimum mean square error

A minimum mean square error, background noise technology, applied in speech analysis, speech recognition, instruments, etc., can solve the problem of not being able to simulate the real situation well

Inactive Publication Date: 2007-11-28
ZTE CORP
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Problems solved by technology

[0012] The key issue of the MMSE method is which statistical model to use to reflect the statistical distribution of the frequency-domain speech signal. The Gaussian model is commonly used in the existing meth

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  • Method for realizing background noise suppressing based on multiple statistics model and minimum mean square error
  • Method for realizing background noise suppressing based on multiple statistics model and minimum mean square error
  • Method for realizing background noise suppressing based on multiple statistics model and minimum mean square error

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Embodiment Construction

[0060] The speech input model of most communication applications has the characteristics of single-channel speech input and additive background noise, and the present invention relates to the noise suppression problem under this model. Aiming at the problem of noise suppression, the present invention proposes an adaptive filtering method based on multiple statistical models. Figure 1 shows the framework principle of the whole method. The present invention uses short-time Fourier transform to transform the input signal into the frequency domain, and then uses the parameters obtained in the previous frame to calculate the estimation of the real and imaginary parts of each frequency component of the voice signal in the current input frame, and then calculates the voice existence probability and corrects the voice Signal estimation, after updating the current parameter estimates, uses the inverse short-time Fourier transform to obtain the suppressed speech.

[0061] The steps of ...

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Abstract

The invention discloses an inhibiting method of background noise based on multiple statistical models and minimum mean square deviation, which comprises the following steps: proceeding short-time Fuliye transmission for voice signal corresponding to present input frame; utilizing the frame to retain the pure voice amplitude variance estimation and noise amplitude variance estimation on each frequency; calculating the estimation of real part and imaginary part corresponding to each frequent component of voice signal in the present frame; counting the probability of non-existed prior voice of each component frequency of the input frame; modifying the estimation result of real part and imaginary part of each frequency component; obtaining the true distribution of voice and noise in the real applying precisely; improving the inhibiting effect with stable estimating course; reducing the calculating complexity; fitting for kinds of voice communicating systems.

Description

technical field [0001] The invention belongs to the field of speech processing, and mainly relates to a background acoustic noise (Acoustic Noise) suppression method based on a multiple statistical model (Multiple Statistical Model) and a minimum mean square error (Minimum Mean Squared Error). Preprocessing for recognition and other applications. Background technique [0002] In most speech communication applications, the input end of the system can only receive noisy speech interfered by background noise. The noise greatly interferes with the quality of speech communication and reduces the clarity and intelligibility of speech. Voice processing modules such as encoding and decoding have adverse effects. [0003] The background noise suppression technology can extract the original speech as pure as possible from the noisy speech. This research belongs to the category of "speech enhancement" in the field of speech processing. Noise suppression helps to improve the perceived...

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Application Information

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IPC IPC(8): G10L21/02G10L15/20G10L21/0232
Inventor 吴颖谦柯昌伟
Owner ZTE CORP
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