Layer-by-layer channel selection method for voice recognition of self-organizing microphone

A channel selection and speech recognition technology, applied in speech recognition, speech analysis, instruments, etc., can solve problems such as unhelpful performance, increased network calculation, and no exploration of channel selection, so as to improve recognition performance and reduce computational complexity. Effect

Pending Publication Date: 2021-11-09
NORTHWESTERN POLYTECHNICAL UNIV +1
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the above methods only consider the channel weight assignment of a small number of self-organizing nodes (no more than 10 microphone nodes), and do not explore the issue of channel selection
When the sound field environment becomes larger and more complex, and there are more self-organizing nodes, on the one hand, bec

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
  • Layer-by-layer channel selection method for voice recognition of self-organizing microphone
  • Layer-by-layer channel selection method for voice recognition of self-organizing microphone
  • Layer-by-layer channel selection method for voice recognition of self-organizing microphone

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0128] DETAILED DESCRIPTION

[0129] This embodiment uses three data sets: librispeech corpus, libri-adhoc-simu dataset in the self-organized microphone array environment based on librispeech simulation, and 40 distributed microphones play back librispeech's libri-adHoc40 in real environments. Each node of the self-organized microphone array of libri-adhoc-simu and libri-adhoc40 is a single microphone, a channel represents a node. Librispeech contains 2484 speakers more than 1,000 hours of English speeches. In the example, 960 hours of data were selected to train the single channel ASR system and selected 10 hours of data for verification.

[0130] For simulation data, libri-adhoc-simu uses librispeech data for 100 hours "Train-100" subset as training data. Use the "dev-clean" subset as the verification data, a total of 10 hours of data. The "Test-Clean" subset is used as two separate test sets, which contain 5 hours of test data, respectively. The length and width of the simulate...

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 layer-by-layer channel selection method for voice recognition of a self-organizing microphone, and the method is based on a conformer voice recognition framework, and the method comprises: (1), an encoder-decoder framework is adopted, an encoder is based on a Conformer framework, a decoder is based on a Transformer framework, and a multi-head attention mechanism is introduced into an encoder-decoder module; (2) for a single-channel voice recognition system, clean voice is adopted for independent training; and (3) for a multi-channel voice recognition system, the voice of each channel is encoded and then the same decoder is shared, a multi-layer flow attention mechanism is trained, and the channels are screened layer by layer. Under a large-scale self-organizing microphone array, compared with other flow attention-based methods, the method provided by the invention is higher in speech recognition accuracy and lower in calculation complexity.

Description

technical field [0001] The invention belongs to the technical field of voice recognition, and in particular relates to a layer-by-layer channel selection method for voice recognition. Background technique [0002] Long-distance speech recognition is an extremely challenging problem. Multi-channel speech recognition based on microphone array is an important way to improve performance. However, when the distance between the speaker and the microphone array increases, the quality of speech will drop sharply, resulting in a physical upper bound for the performance of Automatic Speech Recognition (ASR) no matter how many channels are added to the array. Self-organizing microphone array is a method to solve the above problems, which includes a series of microphone nodes randomly scattered in the sound field, and the microphone node can be a microphone or a microphone array. Using channel weight assignment and channel selection, the microphones around the speaker can be automatic...

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): G10L15/06G10L15/26G10L19/008G10L21/0216
CPCG10L15/063G10L15/26G10L19/008G10L21/0216G10L2021/02166
Inventor 张晓雷陈俊淇
Owner NORTHWESTERN POLYTECHNICAL UNIV
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