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ON-TRAC' systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks

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 Université), LIG (Université Grenoble Alpes), LIUM (Le Mans Université), and researchers from Airbus. A pipeline approach was explored for the lowresource 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 use of a dual-decoder Transformer that jointly transcribes and translates an input speech signal. This model was trained in order to translate from multiple source languages to multiple target ones.
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https://hal.archives-ouvertes.fr/hal-03298854
Contributor : Natalia Tomashenko <>
Submitted on : Thursday, July 29, 2021 - 3:34:22 AM
Last modification on : Friday, July 30, 2021 - 4:00:54 AM

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Hang Le, Florentin Barbier, Ha Nguyen, Natalia Tomashenko, Salima Mdhaffar, et al.. ON-TRAC' systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks. International Conference on Spoken Language Translation (IWSLT), Aug 2021, Bangkok (virtual), Thailand. ⟨10.18653/v1/2021.iwslt-1.20⟩. ⟨hal-03298854v2⟩

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