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

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 Universite), LIG (Universite Grenoble Alpes), LIUM (Le Mans Universite), 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 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.