Publication Details

13 years of speaker recognition research at BUT, with longitudinal analysis of NIST SRE

MATĚJKA, P.; PLCHOT, O.; GLEMBEK, O.; BURGET, L.; ROHDIN, J.; ZEINALI, H.; MOŠNER, L.; SILNOVA, A.; NOVOTNÝ, O.; DIEZ SÁNCHEZ, M.; ČERNOCKÝ, J. 13 years of speaker recognition research at BUT, with longitudinal analysis of NIST SRE. COMPUTER SPEECH AND LANGUAGE, 2020, vol. 2020, no. 63, p. 1-15. ISSN: 0885-2308.
Czech title
13 let výzkumu rozpoznávání řečníka na VUT s dlouhodobou analýzou na NIST SRE
Type
journal article
Language
English
Authors
URL
Keywords

Speaker recognition, NIST, Evaluations, GMM, Eigen-channel, compensation, JFA,
I-vectors, DNN Embedding, X-vectors

Abstract

In this paper, we present a brief history and a "longitudinal study" of all
important milestone modelling techniques used in text independent speaker
recognition since Brno University of Technology (BUT) first participated in the
NIST Speaker Recognition Evaluation (SRE) in 2006-GMM MAP, GMM MAP with
eigen-channel adaptation, Joint Factor Analysis, i-vector and DNN embedding
(x-vector). To emphasize the historical context, the techniques are evaluated on
all NIST SRE sets since 2004 on a time-machine principle, i.e. a system is always
trained using all data available up till the year of evaluation. Moreover, as
user-contributed audiovisual content dominates nowadays Internet, we
representatively include the Speakers In The Wild (SITW) and VOiCES challenge
datasets in the evaluation of our systems. Not only we present a comparison of
the modelling techniques, but we also show the effect of sampling frequency.

Published
2020
Pages
1–15
Journal
COMPUTER SPEECH AND LANGUAGE, vol. 2020, no. 63, ISSN 0885-2308
DOI
UT WoS
000534481900003
EID Scopus
BibTeX
@article{BUT162674,
  author="Pavel {Matějka} and Oldřich {Plchot} and Ondřej {Glembek} and Lukáš {Burget} and Johan Andréas {Rohdin} and Hossein {Zeinali} and Ladislav {Mošner} and Anna {Silnova} and Ondřej {Novotný} and Mireia {Diez Sánchez} and Jan {Černocký}",
  title="13 years of speaker recognition research at BUT, with longitudinal analysis of NIST SRE",
  journal="COMPUTER SPEECH AND LANGUAGE",
  year="2020",
  volume="2020",
  number="63",
  pages="1--15",
  doi="10.1016/j.csl.2019.101035",
  issn="0885-2308",
  url="https://www.sciencedirect.com/science/article/pii/S0885230819302797?via%3Dihub"
}
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