Dereverberation and Beamforming in Robust Far-Field Speaker Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU130795" target="_blank" >RIV/00216305:26230/18:PU130795 - isvavai.cz</a>
Result on the web
<a href="https://www.isca-speech.org/archive/Interspeech_2018/abstracts/2306.html" target="_blank" >https://www.isca-speech.org/archive/Interspeech_2018/abstracts/2306.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.21437/Interspeech.2018-2306" target="_blank" >10.21437/Interspeech.2018-2306</a>
Alternative languages
Result language
angličtina
Original language name
Dereverberation and Beamforming in Robust Far-Field Speaker Recognition
Original language description
This paper deals with robust speaker verification (SV) in farfield sensing. The robustness is verified on a subset of NIST SRE 2010 corpus retransmitted in multiple real rooms of different acoustics and captured with multiple microphones. We experimented with various data preprocessing steps including different approaches to dereverberation and beamforming applied to ad-hoc microphone arrays. We found that significant improvements in accuracy can be achieved with neural network based generalized eigenvalue beamformer preceded by weighted prediction error dereverberation. We also explored the effect of data augmentation by adding various real or simulated room acoustic properties to the Probabilistic Linear Discriminant Analysis (PLDA) training dataset. As a result, we developed a speaker recognition system whose performance is stable across different room acoustic conditions. It yields 41.4% relative improvement in performance over the system without multi-channel processing tested on the cleanest microphone data. With the best combination of data preprocessing and augmentation, we obtained a performance close to the one we achieved with the original clean test data.
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
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Interspeech 2018
ISBN
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ISSN
1990-9772
e-ISSN
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Number of pages
5
Pages from-to
1334-1338
Publisher name
International Speech Communication Association
Place of publication
Hyderabad
Event location
Hyderabad, India
Event date
Sep 2, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000465363900279