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A speech enhancement method based on deep learning assisted rls filter processing

A filter processing and voice enhancement technology, which is applied in voice analysis, instruments, etc., can solve the problems of reducing microphone beam signal processing power and enhancing voice signals, so as to improve voice recognition rate and human-computer interaction experience, and enhance voice signals , the effect of reducing noise residue

Active Publication Date: 2021-12-17
成都启英泰伦科技有限公司
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Problems solved by technology

[0004] In order to overcome the defects in the prior art, the present invention discloses a speech enhancement method based on deep learning assisted RLS filter processing, which effectively reduces the computing power of microphone beam signal processing, and can reduce the output without increasing distortion Noise residue in the signal, enhance the speech signal, thereby improving the speech recognition rate

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  • A speech enhancement method based on deep learning assisted rls filter processing
  • A speech enhancement method based on deep learning assisted rls filter processing
  • A speech enhancement method based on deep learning assisted rls filter processing

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Embodiment Construction

[0021] Specific embodiments of the present invention will be further described in detail below.

[0022] The speech enhancement method based on deep learning assisted RLS filter processing of the present invention, comprises the following steps:

[0023] S1. The beamforming method of generalized sidelobe cancellation is used to process the microphone array voice signal y(l,k) to obtain the fixed beamforming output signal y s (l,k) and noise reference signal u(l,k); l, k denote time and frequency index respectively;

[0024] S2. Randomly extract the feature signal of any microphone signal in the microphone array and send it to the GRU-Mask network to calculate the masking value mask (l, k) of the original microphone signal;

[0025] S3. Compare the masking value mask(l,k) output by the GRU-Mask network with the noise threshold thred:

[0026] When mask(l,k)0 (l,k) for a fixed beamforming output signal y s (l,k) do filtering processing, the processed signal is used as the fin...

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Abstract

A speech enhancement method based on deep learning-assisted RLS filtering processing, comprising the following steps: S1. Use a beamforming method of generalized sidelobe cancellation to process speech signals to obtain a fixed beamforming output signal and a noise reference signal; S2. Randomize Extract the characteristic signal of any microphone signal in the microphone array and send it to the GRU-Mask network to calculate the masking value of the original microphone signal S3. Compare the masking value output by the network with the noise threshold, calculate the noise canceller, and use the noise canceller to perform noise eliminate. The present invention only uses the RLS algorithm to filter the signal dominated by the noise component, which effectively reduces the computing power of the microphone beam signal processing, and can reduce the noise residue in the output signal without increasing the distortion, so as to enhance the speech signal and improve the The purpose of speech recognition rate and human-computer interaction experience.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and relates to speech recognition, in particular to a speech enhancement method based on deep learning-assisted RLS filter processing. Background technique [0002] With the wide application of voice interaction technology, the traditional single-microphone voice enhancement method can no longer meet the needs of voice quality in interactive technology. For example, in far-field environments or noisy environments, the information captured by single-microphone methods is limited and the noise reduction performance is limited. At this time, using the microphone array signal can effectively use the directional information of the voice signal to capture the voice signal in the beam, suppress the signals of other beams, and obtain a better noise reduction effect. [0003] As one of the classic beamforming algorithms, the General Sidelobe Canceller (GSC) method is widely used. However,...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L21/0208G10L21/0216
CPCG10L21/0208G10L21/0216G10L2021/02166
Inventor 万东琴胡岸刘文通曾帆
Owner 成都启英泰伦科技有限公司
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