Detail publikačního výsledku

Description and Analysis of ABC Submission to NIST LRE 2022

MATĚJKA, P.; SILNOVA, A.; SLAVÍČEK, J.; MOŠNER, L.; PLCHOT, O.; KLČO, M.; PENG, J.; STAFYLAKIS, T.; BURGET, L.

Originální název

Description and Analysis of ABC Submission to NIST LRE 2022

Anglický název

Description and Analysis of ABC Submission to NIST LRE 2022

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This paper summarizes our efforts in the NIST Language Recognition Evaluations 2022 resulting in systems providing competitive performance. We provide both the description and analysis of the systems. We describe what data we have used to train our models, and we follow with embedding extractors and back-end classifiers. After covering the architecture, we concentrate on post-evaluation analysis. We compare different topologies of DNN, different backend classifiers, and the impact of the data used to train them. We also report results with XLS-R pre-trained models. We present the performance of the systems in the Fixed condition, where participants are required to use only predefined data sets, and also in the Open condition allowing to use any data to train the systems.

Anglický abstrakt

This paper summarizes our efforts in the NIST Language Recognition Evaluations 2022 resulting in systems providing competitive performance. We provide both the description and analysis of the systems. We describe what data we have used to train our models, and we follow with embedding extractors and back-end classifiers. After covering the architecture, we concentrate on post-evaluation analysis. We compare different topologies of DNN, different backend classifiers, and the impact of the data used to train them. We also report results with XLS-R pre-trained models. We present the performance of the systems in the Fixed condition, where participants are required to use only predefined data sets, and also in the Open condition allowing to use any data to train the systems.

Klíčová slova

nguage detection, language recognition, embedding extractor, LRE, NIST

Klíčová slova v angličtině

nguage detection, language recognition, embedding extractor, LRE, NIST

Autoři

MATĚJKA, P.; SILNOVA, A.; SLAVÍČEK, J.; MOŠNER, L.; PLCHOT, O.; KLČO, M.; PENG, J.; STAFYLAKIS, T.; BURGET, L.

Rok RIV

2024

Vydáno

20.08.2023

Nakladatel

International Speech Communication Association

Místo

Dublin

Kniha

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

ISSN

1990-9772

Periodikum

Proceedings of Interspeech

Svazek

2023

Číslo

08

Stát

Francouzská republika

Strany od

511

Strany do

515

Strany počet

5

URL

https://www.isca-speech.org/archive/pdfs/interspeech_2023/matejka23_interspeech.pdf

BibTex

@inproceedings{BUT185574,
  author="MATĚJKA, P. and SILNOVA, A. and SLAVÍČEK, J. and MOŠNER, L. and PLCHOT, O. and KLČO, M. and PENG, J. and STAFYLAKIS, T. and BURGET, L.",
  title="Description and Analysis of ABC Submission to NIST LRE 2022",
  booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
  year="2023",
  journal="Proceedings of Interspeech",
  volume="2023",
  number="08",
  pages="511--515",
  publisher="International Speech Communication Association",
  address="Dublin",
  doi="10.21437/Interspeech.2023-1529",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/pdfs/interspeech_2023/matejka23_interspeech.pdf"
}

Dokumenty

matejka23_interspeech2023_description