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A Speech Enhancement System Based on Temporal Modeling Generative Adversarial Networks

A first-time, time-sensitive technology, applied in biological neural network models, speech analysis, instruments, etc., can solve the problems of time dependence of speech time-domain features and insufficient consideration of global aspects, and achieve reliable design principles, wide application prospects, simple structure

Active Publication Date: 2022-07-05
QILU UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides a speech enhancement system based on temporal modeling to generate an adversarial network to solve the problem of insufficient consideration of the time-dependence and global aspects of generating adversarial network speech time-domain features

Method used

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  • A Speech Enhancement System Based on Temporal Modeling Generative Adversarial Networks
  • A Speech Enhancement System Based on Temporal Modeling Generative Adversarial Networks
  • A Speech Enhancement System Based on Temporal Modeling Generative Adversarial Networks

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Embodiment Construction

[0036] In order to make those skilled in the art better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] Key terms appearing in the present invention are explained below.

[0038] GRU: Gated Recurrent Unit, a gated recurrent unit, uses a gated mechanism to control information such as input and memory, and makes predictions at the current time.

[0039] figure 1 Shown is a speech enhancement system based on temporal m...

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Abstract

The invention provides a speech enhancement system based on a time modeling generative adversarial network, belonging to the technical field of speech signal processing, comprising: a data acquisition unit for acquiring a noisy speech signal and down-sampling the noisy speech signal; The signal enhancement unit is used for inputting the noisy speech signal into a generative adversarial network based on time modeling, compressing and extracting the global time domain feature of the speech signal, linking the time domain feature and random noise into a feature vector, and correcting the The feature vector is decoded to obtain an enhanced speech signal. The invention solves the problems of insufficient time dependence and global consideration of speech time domain features, reduces the influence of noise in the speech signal, and improves the hearing quality of the enhanced speech.

Description

technical field [0001] The invention belongs to the technical field of speech signal processing, and in particular relates to a speech enhancement system based on a temporal modeling generative confrontation network. Background technique [0002] Speech enhancement is a key technology to improve speech quality and intelligibility, that is, a technology that uses audio signal processing technology to remove noise and extract pure speech signals from an observation signal containing noise. Introducing significant speech distortion remains a formidable challenge. [0003] In recent years, with the rapid development of artificial intelligence technology and computer processing capabilities, deep learning has become a hot technology in many research fields and has achieved many remarkable research results. Because of the limited performance of traditional speech enhancement algorithms such as Wiener filtering and spectral subtraction, deep learning technology has been introduced...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L21/02G10L25/30G06N3/04
CPCG10L21/02G10L25/30G06N3/045
Inventor 董安明张德辉禹继国韩玉冰李素芳张丽邱静刘洋张滕刘宗银
Owner QILU UNIV OF TECH
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