Detail výsledku

Multilingually Trained Bottleneck Features in Spoken Language Recognition

FÉR, R.; MATĚJKA, P.; GRÉZL, F.; PLCHOT, O.; VESELÝ, K.; ČERNOCKÝ, J. Multilingually Trained Bottleneck Features in Spoken Language Recognition. COMPUTER SPEECH AND LANGUAGE, 2017, vol. 2017, no. 46, p. 252-267. ISSN: 0885-2308.
Typ
článek v časopise
Jazyk
anglicky
Autoři
Fér Radek, Ing.
Matějka Pavel, Ing., Ph.D., UPGM (FIT)
Grézl František, Ing., Ph.D., UPGM (FIT)
Plchot Oldřich, Ing., Ph.D., UPGM (FIT)
Veselý Karel, Ing., Ph.D., UPGM (FIT)
Černocký Jan, prof. Dr. Ing., UPGM (FIT)
Abstrakt

Multilingual training of neural networks has proven to be simple yet effective way to deal with multilingual training corpora. It allows to use several resources to jointly train a language independent representation of features, which can be encoded into low-dimensional feature set by embedding narrow bottleneck layer to the network. In this paper, we analyze such features on the task of spoken language recognition (SLR), focusing on practical aspects of training bottleneck networks and analyzing their integration in SLR. By comparing properties of mono and multilingual features we show the suitability of multilingual training for SLR. The state-of-the-art performance of these features is demonstrated on the NIST LRE09 database.

Klíčová slova

Multilingual training, Bottleneck features, Spoken language recognition

URL
Rok
2017
Strany
252–267
Časopis
COMPUTER SPEECH AND LANGUAGE, roč. 2017, č. 46, ISSN 0885-2308
DOI
UT WoS
000407609600015
EID Scopus
BibTeX
@article{BUT144471,
  author="Radek {Fér} and Pavel {Matějka} and František {Grézl} and Oldřich {Plchot} and Karel {Veselý} and Jan {Černocký}",
  title="Multilingually Trained Bottleneck Features in Spoken Language Recognition",
  journal="COMPUTER SPEECH AND LANGUAGE",
  year="2017",
  volume="2017",
  number="46",
  pages="252--267",
  doi="10.1016/j.csl.2017.06.008",
  issn="0885-2308",
  url="http://www.sciencedirect.com/science/article/pii/S0885230816302947"
}
Soubory
Projekty
IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, zahájení: 2016-01-01, ukončení: 2020-12-31, ukončen
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