@inproceedings{le-etal-2021-trac,
title = "{ON}-{TRAC}{'} systems for the {IWSLT} 2021 low-resource speech translation and multilingual speech translation shared tasks",
author = "Le, Hang and
Barbier, Florentin and
Nguyen, Ha and
Tomashenko, Natalia and
Mdhaffar, Salima and
Gahbiche, Souhir Gabiche and
Lecouteux, Benjamin and
Schwab, Didier and
Est{\`e}ve, Yannick",
editor = "Federico, Marcello and
Waibel, Alex and
Costa-juss{\`a}, Marta R. and
Niehues, Jan and
Stuker, Sebastian and
Salesky, Elizabeth",
booktitle = "Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)",
month = aug,
year = "2021",
address = "Bangkok, Thailand (online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.iwslt-1.20",
doi = "10.18653/v1/2021.iwslt-1.20",
pages = "169--174",
abstract = "This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2021, low-resource speech translation and multilingual speech translation. The ON-TRAC Consortium is composed of researchers from three French academic laboratories and an industrial partner: LIA (Avignon Universit{\'e}), LIG (Universit{\'e} Grenoble Alpes), LIUM (Le Mans Universit{\'e}), and researchers from Airbus. A pipeline approach was explored for the low-resource speech translation task, using a hybrid HMM/TDNN automatic speech recognition system fed by wav2vec features, coupled to an NMT system. For the multilingual speech translation task, we investigated the us of a dual-decoder Transformer that jointly transcribes and translates an input speech. This model was trained in order to translate from multiple source languages to multiple target ones.",
}
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%0 Conference Proceedings
%T ON-TRAC’ systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks
%A Le, Hang
%A Barbier, Florentin
%A Nguyen, Ha
%A Tomashenko, Natalia
%A Mdhaffar, Salima
%A Gahbiche, Souhir Gabiche
%A Lecouteux, Benjamin
%A Schwab, Didier
%A Estève, Yannick
%Y Federico, Marcello
%Y Waibel, Alex
%Y Costa-jussà, Marta R.
%Y Niehues, Jan
%Y Stuker, Sebastian
%Y Salesky, Elizabeth
%S Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand (online)
%F le-etal-2021-trac
%X This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2021, low-resource speech translation and multilingual speech translation. The ON-TRAC Consortium is composed of researchers from three French academic laboratories and an industrial partner: LIA (Avignon Université), LIG (Université Grenoble Alpes), LIUM (Le Mans Université), and researchers from Airbus. A pipeline approach was explored for the low-resource speech translation task, using a hybrid HMM/TDNN automatic speech recognition system fed by wav2vec features, coupled to an NMT system. For the multilingual speech translation task, we investigated the us of a dual-decoder Transformer that jointly transcribes and translates an input speech. This model was trained in order to translate from multiple source languages to multiple target ones.
%R 10.18653/v1/2021.iwslt-1.20
%U https://aclanthology.org/2021.iwslt-1.20
%U https://doi.org/10.18653/v1/2021.iwslt-1.20
%P 169-174
Markdown (Informal)
[ON-TRAC’ systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks](https://aclanthology.org/2021.iwslt-1.20) (Le et al., IWSLT 2021)
ACL
- Hang Le, Florentin Barbier, Ha Nguyen, Natalia Tomashenko, Salima Mdhaffar, Souhir Gabiche Gahbiche, Benjamin Lecouteux, Didier Schwab, and Yannick Estève. 2021. ON-TRAC’ systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks. In Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021), pages 169–174, Bangkok, Thailand (online). Association for Computational Linguistics.