End-to-end voice enhancing method based on RefineNet

A speech enhancement and speech signal technology, applied in speech analysis, instruments, etc., can solve the problems of ignoring phase information, enhancing speech clarity and intelligibility, etc.

Active Publication Date: 2019-09-17
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Claims
  • Application Information

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Problems solved by technology

[0004] In view of the above-mentioned deficiencies in the prior art, the end-to-end speech enhancement method based on RefineNet provided by the present

Method used

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  • End-to-end voice enhancing method based on RefineNet

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Embodiment Construction

[0102] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0103] Such as figure 1 As shown, an end-to-end speech enhancement method based on RefineNet includes the following steps:

[0104] S1. Transform the original noisy speech signal into a feature map containing time-frequency information through the TFANet time-frequency analysis network, and input it into the RefineNet network;

[0105] S2. Analyze the feature map through the RefineNet network to determine the feature map c...

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Abstract

The invention discloses an end-to-end voice enhancing method based on RefineNet. Firstly, a time-frequency analysis network is constructed to carry out coding analysis on voice signals, then the RefineNet is used for learning the characteristic mapping from noisy voice to pure voice, and finally, enhanced voice signals are generated through decoding. On the basis, an improved method for fusing evaluation indexes with a training loss function and a multi-objective fusion learning strategy for simultaneously taking an STOI and an SDR as optimization targets are provided. In tests under different noise environments and different signal-to-noise ratios, the indexes of the method provided by the invention are obviously superior to those of representative traditional methods and non-end-to-end and end-to-end deep learning methods in the aspects of the STOI, the PESQ and the SDR, the definition and the intelligibility of voice can be better improved, and a better voice enhancement effect is achieved.

Description

technical field [0001] The invention belongs to the technical field of speech signal processing, and specifically designs an end-to-end speech enhancement method based on RefineNet. Background technique [0002] The main goal of speech signal enhancement is to extract the original speech signal from noisy speech, and to improve the perceived quality and intelligibility of speech by suppressing or separating noise. application. After several decades of development, many speech enhancement algorithms have been proposed one after another. Classical speech enhancement techniques mainly include spectral subtraction, Wiener filtering, methods based on statistical models, etc. These methods are often based on the assumption that the noise is stationary. The enhancement effect deteriorates sharply in the case of smooth noise. [0003] The rise of deep learning and its successful application in the fields of image classification, speech recognition, and natural speech processing ha...

Claims

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Application Information

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IPC IPC(8): G10L19/02G10L21/0224G10L21/0232G10L25/27
CPCG10L19/02G10L21/0224G10L21/0232G10L25/27
Inventor 蓝天彭川李森刘峤钱宇欣叶文政李萌惠国强吕忆蓝
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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