Speech enhancement method based on gated cycle encoding and decoding network

Abstract

The invention relates to a speech enhancement method based on a gated cycle encoding and decoding network, and relates to the technical field of speech enhancement. According to the method, the speechenhancement method based on the gated cycle encoding and decoding network is proposed based on the research of the process of human auditory perception aiming at the problem that the conventional speech enhancement method does not employ the connection between context information and a current to-be-enhanced speech frame. In a speech enhancement task, an encoding and decoding architecture is introduced, modeling of multiple adjacent frames of speech signals is performed by employing an encoder to extract the context information, mining of the connection between the current to-be-enhanced speech frame and the context information is performed by employing a decoder, and the speech enhancement performance is improved.

Description

technical field [0001] The invention relates to the technical field of speech enhancement, in particular to a speech enhancement method based on a gated loop codec network. Background technique [0002] Speech enhancement technology, as a basic link in the signal processing process, has broad application prospects in many fields such as speech recognition, mobile communication and artificial hearing. Its main purpose is to improve the quality and intelligibility of noise-contaminated speech. Recently, with the rise of deep learning technology, supervised speech enhancement methods based on Deep Neural Network (DNN) have achieved great success, especially in the case of low SNR and non-stationary noise, compared with Compared with the traditional method, it shows a stronger advantage. [0003] From the perspective of supervised learning, the speech enhancement method based on deep learning mainly includes three parts: features, network model and optimization objective. Amp...

AI Technical Summary

Problems solved by technology

[0004] However, the current speech enhancement methods based on deep learning usually only use the context information, but ignore the connection between the context information and the current speech frame to be enhanced.

Images