Publication detail
Speaker Verification Using End-To-End Adversarial Language Adaptation
ROHDIN, J. STAFYLAKIS, T. SILNOVA, A. ZEINALI, H. BURGET, L. PLCHOT, O.
Original Title
Speaker Verification Using End-To-End Adversarial Language Adaptation
Type
conference paper
Language
English
Original Abstract
In this paper we investigate the use of adversarial domainadaptation for addressing the problem of language mismatchbetween speaker recognition corpora. In the context ofspeaker verification, adversarial domain adaptation methodsaim at minimizing certain divergences between the distributionthat the utterance-level features follow (i.e. speakerembeddings) when drawn from source and target domains(i.e. languages), while preserving their capacity in recognizingspeakers. Neural architectures for extracting utterancelevelrepresentations enable us to apply adversarial adaptationmethods in an end-to-end fashion and train the networkjointly with the standard cross-entropy loss. We examineseveral configurations, such as the use of (pseudo-)labels onthe target domain as well as domain labels in the feature extractor,and we demonstrate the effectiveness of our methodon the challenging NIST SRE16 and SRE18 benchmarks.
Keywords
Speaker recognition, domain adaptation
Authors
ROHDIN, J.; STAFYLAKIS, T.; SILNOVA, A.; ZEINALI, H.; BURGET, L.; PLCHOT, O.
Released
12. 5. 2019
Publisher
IEEE Signal Processing Society
Location
Brighton
ISBN
978-1-5386-4658-8
Book
Proceedings of ICASSP 2019
Pages from
6006
Pages to
6010
Pages count
5
URL
BibTex
@inproceedings{BUT158086,
author="Johan Andréas {Rohdin} and Themos {Stafylakis} and Anna {Silnova} and Hossein {Zeinali} and Lukáš {Burget} and Oldřich {Plchot}",
title="Speaker Verification Using End-To-End Adversarial Language Adaptation",
booktitle="Proceedings of ICASSP 2019",
year="2019",
pages="6006--6010",
publisher="IEEE Signal Processing Society",
address="Brighton",
doi="10.1109/ICASSP.2019.8683616",
isbn="978-1-5386-4658-8",
url="https://ieeexplore.ieee.org/abstract/document/8683616"
}
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