Network model training method, echo cancellation method and equipment

A training method and echo cancellation technology, applied in biological neural network models, neural learning methods, character and pattern recognition, etc., can solve problems such as inability to accurately estimate residual echo, near-end speech distortion, and low letter-to-return ratio

Pending Publication Date: 2021-12-03
ZHEJIANG DAHUA TECH CO LTD
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in scenarios with low signal-to-return ratio and strong nonlinear distortion, the traditional echo cancellation algorithm cannot accurately est

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Network model training method, echo cancellation method and equipment
  • Network model training method, echo cancellation method and equipment
  • Network model training method, echo cancellation method and equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] In order to make the purpose, technical solution and effect of the present application more clear and definite, the present application will be further described in detail below with reference to the accompanying drawings and examples.

[0026] It should be noted that if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for description purposes, and should not be understood as indicate or imply their relative importance or implicitly indicate the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of these features. In addition, the technical solutions of the various embodiments can be combined with each other, but it must be based on the realization of those skilled in the art. When the combination of technical solutions is contradictory or cannot be realized, it should be con...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a recurrent neural network model training method, an echo cancellation method, terminal equipment and a computer readable storage medium. The method comprises the steps: obtaining a sample signal which comprises a microphone signal and a reference signal corresponding to the microphone signal; carrying out feature extraction on the sample signal to obtain a first acoustic feature and a second acoustic feature, wherein the first acoustic feature is the acoustic feature of the microphone signal, and the second acoustic feature is the acoustic feature of the reference signal; inputting the first acoustic feature and the second acoustic feature into an initial recurrent neural network model, and outputting a predicted value of a phase sensitive mask, wherein the phase sensitive mask is a frequency spectrum proportion of an echo cancellation signal in the microphone signal, and a frequency spectrum comprises an amplitude spectrum and a phase spectrum; and calculating loss of the phase sensitive mask to adjust parameters of the initial recurrent neural network model to obtain the recurrent neural network model. In this way, the echo cancellation capability can be improved.

Description

technical field [0001] The present application relates to the technical field of echo cancellation, in particular to a training method of a cyclic neural network model, an echo cancellation method, a terminal device and a computer-readable storage medium. Background technique [0002] In video conferencing systems, due to the high-level coupling of microphones and speakers, acoustic echoes that affect voice interactions often occur. In traditional echo cancellation, the acoustic path from the speaker to the microphone in the acoustic environment is estimated through a finite-length linear filter to eliminate the linear echo, and then a gain value is applied to remove the remaining residual echo. However, in scenarios with low signal-to-return ratio and strong nonlinear distortion, the traditional echo cancellation algorithm cannot accurately estimate the residual echo, resulting in the inability of the video conferencing system to suppress the residual echo and cause near-en...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G10L21/0208G10L21/0232G10L25/18G10L25/30G06K9/00G06N3/04G06N3/08
CPCG10L21/0208G10L21/0232G10L25/18G10L25/30G06N3/04G06N3/08G10L2021/02082G06F2218/08
Inventor 吴人杰黄景标林聚财殷俊
Owner ZHEJIANG DAHUA TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap