Multi-Channel Speaker Verification with Conv-Tasnet Based Beamformer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU144909" target="_blank" >RIV/00216305:26230/22:PU144909 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9747771" target="_blank" >https://ieeexplore.ieee.org/document/9747771</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP43922.2022.9747771" target="_blank" >10.1109/ICASSP43922.2022.9747771</a>
Alternative languages
Result language
angličtina
Original language name
Multi-Channel Speaker Verification with Conv-Tasnet Based Beamformer
Original language description
We focus on the problem of speaker recognition in far-field multichannel data. The main contribution is introducing an alternative way of predicting spatial covariance matrices (SCMs) for a beamformer from the time domain signal. We propose to use ConvTasNet, a well-known source separation model, and we adapt it to perform speech enhancement by forcing it to separate speech and additive noise. We experiment with using the STFT of Conv-TasNet outputs to obtain SCMs of speech and noise, and finally, we fine-tune this multi-channel frontend w.r.t. speaker verification objective. We successfully tackle the problem of the lack of a realistic multichannel training set by using simulated data of MultiSV corpus. The analysis is performed on its retransmitted and simulated test parts. We achieve consistent improvements with a 2.7 times smaller model than the baseline based on a scheme with mask estimating NN.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISBN
978-1-6654-0540-9
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
7982-7986
Publisher name
IEEE Signal Processing Society
Place of publication
Singapore
Event location
Singapore
Event date
May 22, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000864187908058