Publication Details

DNN-based SRE Systems in Multi-Language Conditions

NOVOTNÝ Ondřej, MATĚJKA Pavel, GLEMBEK Ondřej, PLCHOT Oldřich, GRÉZL František, BURGET Lukáš and ČERNOCKÝ Jan. DNN-based SRE Systems in Multi-Language Conditions. Brno: Faculty of Information Technology BUT, 2016. Available from: http://www.fit.vutbr.cz/research/groups/speech/publi/2016/dnn-based-sre_TECH_REP_v0.pdf
Czech title
Systémy pro rozpoznávání mluvčího založené na DNN v multilingválních podmínkách
Type
report
Language
english
Authors
Novotný Ondřej, Ing., Ph.D. (DCGM FIT BUT)
Matějka Pavel, Ing., Ph.D. (DCGM FIT BUT)
Glembek Ondřej, Ing., Ph.D. (DCGM FIT BUT)
Plchot Oldřich, Ing., Ph.D. (DCGM FIT BUT)
Grézl František, Ing., Ph.D. (DCGM FIT BUT)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT)
URL
Keywords

speaker recognition, multilinguality, DNN

Abstract

This work studies the usage of the (currently state-of-the-art) Deep Neural Networks (DNN) i-vector/PLDA-based speaker recognition systems in multi-language (especially non-English) conditions. On the ``Language Pack'' of the PRISM set, we evaluate the systems' performance using NIST's standard metrics. We study the use of multi-lingual DNN in place of the original English DNN on these multi-language conditions. We show that not only the gain from using DNNs vanishes, but also the DNN-based systems tend to produce de-calibrated scores under the studied conditions. This work gives suggestions for directions of future research rather than any particular solutions.

Annotation

This work studies the usage of the (currently state-of-the-art) Deep Neural Networks (DNN) i-vector/PLDA-based speaker recognition sys- tems in multi-language (especially non-English) conditions. On the "Lan- guage Pack" of the PRISM set, we evaluate the systems performance using NISTs standard metrics. We study the use of multi-lingual DNN in place of the original English DNN on these multi-language conditions. We show that not only the gain from using DNNs vanishes, but also the DNN-based systems tend to produce de-calibrated scores under the studied conditions. This work gives suggestions for directions of future research rather than any particular solutions.

Published
2016
Pages
5
Publisher
Faculty of Information Technology BUT
Place
Brno, CZ
BibTeX 
@TECHREPORT{FITPUB11235,
   author = "Ond\v{r}ej Novotn\'{y} and Pavel Mat\v{e}jka and Ond\v{r}ej Glembek and Old\v{r}ich Plchot and Franti\v{s}ek Gr\'{e}zl and Luk\'{a}\v{s} Burget and Jan \v{C}ernock\'{y}",
   title = "DNN-based SRE Systems in Multi-Language Conditions",
   pages = 5,
   year = 2016,
   location = "Brno, CZ",
   publisher = "Faculty of Information Technology BUT",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11235"
}
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