Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A voiceprint recognition method and system based on variational information bottleneck

A voiceprint recognition and information bottleneck technology, which is applied in the field of voiceprint recognition methods and systems based on variational information bottlenecks, can solve the problem of low accuracy of voiceprint recognition, improve recognition accuracy, improve robustness, reduce The effect of feature redundancy

Active Publication Date: 2022-07-19
WUHAN UNIV OF TECH
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention proposes a voiceprint recognition method and system based on a variational information bottleneck, which is used to solve or at least partially solve the technical problem of low voiceprint recognition accuracy in practical application scenarios

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
  • A voiceprint recognition method and system based on variational information bottleneck
  • A voiceprint recognition method and system based on variational information bottleneck
  • A voiceprint recognition method and system based on variational information bottleneck

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0048] The embodiment of the present invention provides a voiceprint recognition method based on variational information bottleneck, including:

[0049] S1: Obtain the original voice data;

[0050] S2: Construct a voiceprint recognition model that introduces a variational information bottleneck, wherein the voiceprint recognition model includes an acoustic feature parameter extraction layer, a frame-level feature extraction network, a feature aggregation layer, a variational information bottleneck layer, and a classifier, wherein the acoustic feature The parameter extraction layer is used to convert the input original speech waveform into the acoustic feature parameter FBank, and the frame-level feature extraction network is used to extract multi-scale and multi-frequency frame-level speaker information from the acoustic feature parameter FBank in a single aggregation method, and obtain frame-level speaker information. Feature vector, the feature aggregation layer is used to c...

Embodiment 2

[0118] Based on the same inventive concept, this embodiment provides a voiceprint recognition system based on variational information bottleneck, including:

[0119] A data acquisition module for acquiring original voice data;

[0120] The model building module is used to construct a voiceprint recognition model that introduces a variational information bottleneck. The voiceprint recognition model includes an acoustic feature parameter extraction layer, a frame-level feature extraction network, a feature aggregation layer, a variational information bottleneck layer, and a classifier. Among them, the acoustic feature parameter extraction layer is used to convert the input original speech waveform into the acoustic feature parameter FBank, and the frame-level feature extraction network is used to extract the multi-scale and multi-frequency frame-level speaker information from the acoustic feature parameter FBank to obtain frame-level speaker information. Feature vector, the feat...

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 present invention provides a voiceprint recognition method and system based on variational information bottleneck, which solves the problems of poor robustness and poor discrimination of speaker embedding extracted by the existing voiceprint recognition model. First, a feature extraction network composed of VovNet and Ultra Lightweight Subspace Attention Mechanism (ULSAM) is proposed to extract multi-scale and multi-frequency frame-level speaker information; then a variational information bottleneck is introduced as a regularization The method further compresses the speaker feature vector, removes the irrelevant information of the speaker, and only retains the information related to the identification of the speaker, so that the final extracted speaker embedding is more robust. Compared with the existing voiceprint recognition technology, the present invention improves the recognition accuracy of the voiceprint recognition in the noise background, so that the voiceprint recognition technology is more suitable for real life scenarios.

Description

technical field [0001] The invention relates to the fields of deep learning and voiceprint recognition, in particular to a voiceprint recognition method and system based on variational information bottlenecks. Background technique [0002] Voiceprint recognition, also known as speaker recognition, is a technology that automatically identifies the speaker's identity based on the speech parameters in the sound waveform that reflect the speaker's physiological and behavioral characteristics. The emergence of deep learning has greatly promoted the development of voiceprint recognition. End-to-end voiceprint recognition based on deep neural networks has become the current mainstream technology, that is, using the powerful learning capabilities of deep neural networks to learn a speech from speech signals. Person representation vector, called speaker embedding. [0003] Voiceprint recognition based on deep speaker embedding usually consists of three parts: feature extraction netw...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G10L17/04G10L17/02G10L17/18G10L17/20G06N3/04G06N3/08
CPCG10L17/04G10L17/02G10L17/18G10L17/20G06N3/084G06N3/045
Inventor 熊盛武王丹董元杰
Owner WUHAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com