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Phase-sensitive gated multi-scale dilated convolutional network speech enhancing method and system

A convolutional network, phase-sensitive technology, applied in speech analysis, instruments, etc., can solve the problems of voice trembling, voice distortion, etc., to achieve the effect of improving the effect, avoiding voice distortion, and good voice intelligibility

Pending Publication Date: 2021-02-02
SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
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Problems solved by technology

However, when our voice products face harsher acoustic scenarios, such as the signal-to-noise ratio is lower than 0dB, or the noise signal completely submerges the voice signal in a local time, it is not possible to only enhance the amplitude of the voice signal. Ensure that the enhanced voice has good speech intelligibility, and there may even be some voice distortion problems such as trembling and humming

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  • Phase-sensitive gated multi-scale dilated convolutional network speech enhancing method and system
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  • Phase-sensitive gated multi-scale dilated convolutional network speech enhancing method and system

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[0019] The present invention will be further described below in conjunction with the description of the drawings and specific embodiments.

[0020] A phase-sensitive gated multi-scale atrous convolutional network speech enhancement method, which aims to use the neural network model to construct the mapping relationship between the complex spectrum of the speech signal, and process the real and imaginary part of the noisy speech spectrum after time-frequency analysis. Mapping, the enhanced real and imaginary part spectrum is obtained, and restored to the enhanced time-domain speech signal. The processing flow of the whole algorithm is as follows figure 1 As shown, the dotted line part is the gated multi-scale atrous convolutional network structure designed in the present invention, which is the core module of the whole algorithm. Noise reduction processing of real and imaginary part spectrum.

[0021] Such as figure 1 As shown, the noisy speech signal is first processed by f...

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Abstract

The invention provides a phase-sensitive gated multi-scale dilated convolutional network speech enhancing method. The method comprises the following steps: constructing a mapping relationship betweencomplex frequency spectrums of speech signals by using a neural network model, mapping a real and imaginary part frequency spectrum of noisy speech subjected to time-frequency analysis processing to obtain an enhanced real and imaginary part frequency spectrum, and recovering the spectrum into an enhanced time domain voice signal. The invention also provides a phase-sensitive gating multi-scale dilated convolutional network speech enhancing system. The method has the beneficial effects that: the method improves the speech enhancement effect, guarantees that the enhanced speech has good speechintelligibility, and better avoids the problem of speech distortion.

Description

technical field [0001] The invention relates to a speech enhancement method, in particular to a phase-sensitive gated multi-scale hole convolution network speech enhancement method and system. Background technique [0002] Early auditory experiments have shown that when the signal-to-noise ratio is higher than 6dB, phase distortion has little effect on speech quality and intelligibility. Therefore, most current single-channel speech enhancement methods mainly perform noise reduction in the amplitude domain of the speech signal. processing, and directly use the noisy phase to reconstruct the speech signal. However, when our voice products are faced with harsher acoustic scenarios, such as signal-to-noise ratios below 0dB, or when noise signals completely submerge voice signals in a local time, it is not possible to only enhance the amplitude of voice signals. Ensure that the enhanced voice has good speech intelligibility, and there may even be some voice distortion problems ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L21/02G10L25/30
CPCG10L25/30Y02T10/40
Inventor 刘明周彦兵唐飞周小明赵学华
Owner SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
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