Detail publikace

BUT- PT System Description for NIST LRE 2017

MATĚJKA, P. PLCHOT, O. NOVOTNÝ, O. CUMANI, S. LOZANO DÍEZ, A. SLAVÍČEK, J. DIEZ SÁNCHEZ, M. GRÉZL, F. GLEMBEK, O. KAMSALI VEERA, M. SILNOVA, A. BURGET, L. ONDEL, L. KESIRAJU, S. ROHDIN, J.

Originální název

BUT- PT System Description for NIST LRE 2017

Anglický název

BUT- PT System Description for NIST LRE 2017

Jazyk

en

Originální abstrakt

This article is about the BUT - PT System Description for the NIST LRE 2017 evaluation. We have built over 30 systems for this evaluation with the main focus to build a  single best system. We experimented with denoising NN, automatic discovery units, different flavors of phonotactic systems, different backends, different sizes of i-vector systems, different BN features, NN embeddings and frame level language classifiers. The evaluation plan stated "Teams are encouraged to report whether and how having access to the development set helped improve the performance". The development data helped mainly in the final classifier and also helped in the decision process which techniques to use and which to fuse because our test set consisted of this data.

Anglický abstrakt

This article is about the BUT - PT System Description for the NIST LRE 2017 evaluation. We have built over 30 systems for this evaluation with the main focus to build a  single best system. We experimented with denoising NN, automatic discovery units, different flavors of phonotactic systems, different backends, different sizes of i-vector systems, different BN features, NN embeddings and frame level language classifiers. The evaluation plan stated "Teams are encouraged to report whether and how having access to the development set helped improve the performance". The development data helped mainly in the final classifier and also helped in the decision process which techniques to use and which to fuse because our test set consisted of this data.

Dokumenty

BibTex


@inproceedings{BUT168463,
  author="Pavel {Matějka} and Oldřich {Plchot} and Ondřej {Novotný} and Sandro {Cumani} and Alicia {Lozano Díez} and Mireia {Diez Sánchez} and František {Grézl} and Ondřej {Glembek} and Mounika {Kamsali Veera} and Anna {Silnova} and Lukáš {Burget} and Lucas Antoine Francois {Ondel} and Santosh {Kesiraju} and Johan Andréas {Rohdin}",
  title="BUT- PT System Description for NIST LRE 2017",
  annote="This article is about the BUT - PT System Description for the NIST LRE 2017
evaluation. We have built over 30 systems for this evaluation with the main focus
to build a  single best system. We experimented with denoising NN, automatic
discovery units, different flavors of phonotactic systems, different backends,
different sizes of i-vector systems, different BN features, NN embeddings and
frame level language classifiers. The evaluation plan stated "Teams are
encouraged to report whether and how having access to the development set helped
improve the performance". The development data helped mainly in the final
classifier and also helped in the decision process which techniques to use and
which to fuse because our test set consisted of this data.",
  address="National Institute of Standards and Technology",
  booktitle="Proceedings of NIST Language Recognition Workshop 2017",
  chapter="168463",
  edition="NEUVEDEN",
  howpublished="electronic, physical medium",
  institution="National Institute of Standards and Technology",
  year="2017",
  month="december",
  pages="1--6",
  publisher="National Institute of Standards and Technology",
  type="conference paper"
}