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ON-TRAC Consortium Systems for the IWSLT 2022 Dialect and Low-resource Speech Translation Tasks. (arXiv:2205.01987v1 [cs.CL])
May 5, 2022, 1:11 a.m. | Marcely Zanon Boito, John Ortega, Hugo Riguidel, Antoine Laurent, Loïc Barrault, Fethi Bougares, Firas Chaabani, Ha Nguyen, Florentin Barbier, So
cs.CL updates on arXiv.org arxiv.org
This paper describes the ON-TRAC Consortium translation systems developed for
two challenge tracks featured in the Evaluation Campaign of IWSLT 2022:
low-resource and dialect speech translation. For the Tunisian Arabic-English
dataset (low-resource and dialect tracks), we build an end-to-end model as our
joint primary submission, and compare it against cascaded models that leverage
a large fine-tuned wav2vec 2.0 model for ASR. Our results show that in our
settings pipeline approaches are still very competitive, and that with the use
of …
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