Perceptual filtering method and perceptual filter

Abstract

The invention provides a perceptual filtering method. The perceptual filtering method includes the following steps that: noise-containing speech is obtained, the noise-containing speech is calculated according to a noise estimation algorithm, so that noise power can be obtained; the noise-containing speech is calculated according to a masking model, so that a frequency-domain masking threshold value can be obtained; the noise-containing speech is converted to a frequency domain, so that frequency-domain noise-containing speech can be obtained, wherein the frequency-domain noise-containing speech includes frequency-domain pure speech and frequency-domain background noises; based on a speech estimation error algorithm, speech signal distortion is expressed as an relational expression about the frequency-domain pure speech and perceptual filter gain, and filtering background noises are expressed as an relational expression about the frequency-domain background noises and the perceptual filter gain; based on a relationship that the sum of the power of the speech signal distortion and the power of the filtering background noises is smaller or equal to the frequency-domain masking threshold value, an equation about the perceptual filter gain can be constructed; the equation is solved, so that the perceptual filter gain can be obtained; and filtering processing is performed on the noise-containing speech according to the perceptual filter gain, so that enhanced speech can be obtained. With the perceptual filtering method adopted, the subjective perceptual quality of the speech can be improved. The invention also provides a perceptual filter.

Description

technical field [0001] The invention relates to the field of speech signal processing, in particular to a perceptual filtering method and a perceptual filter. Background technique [0002] Speech signals are inevitably polluted by background noise in real life. As a signal processing method, speech enhancement is an efficient way to solve noise pollution, so it has always been a research hotspot in the field of speech signal processing. The purpose of speech enhancement is to remove background noise as much as possible and improve the subjective auditory effect of speech on the premise of ensuring speech intelligibility. [0003] Traditional speech enhancement algorithms include spectral subtraction, Wiener filtering, minimum mean square error estimation, logarithmic spectral amplitude minimum mean square error, enhancement methods based on DCT (Discrete Cosine Transform, discrete cosine) transform, etc. Most of these methods are based on statistical models of speech and no...

AI Technical Summary

Problems solved by technology

However, due to the deviation between the assumed model and the actual situation in the traditional speech enhancement algorithm, there are still a lot of speech distortion and residual noise in the enhanced speech signal, which affects the effect of speech enhancement.

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