CUNI Neural ASR with Phoneme-Level Intermediate Step for~Non-Native~SLT at IWSLT 2020

Peter Polák, Sangeet Sagar, Dominik Macháček, Ondřej Bojar


Abstract
In this paper, we present our submission to the Non-Native Speech Translation Task for IWSLT 2020. Our main contribution is a proposed speech recognition pipeline that consists of an acoustic model and a phoneme-to-grapheme model. As an intermediate representation, we utilize phonemes. We demonstrate that the proposed pipeline surpasses commercially used automatic speech recognition (ASR) and submit it into the ASR track. We complement this ASR with off-the-shelf MT systems to take part also in the speech translation track.
Anthology ID:
2020.iwslt-1.24
Volume:
Proceedings of the 17th International Conference on Spoken Language Translation
Month:
July
Year:
2020
Address:
Online
Venues:
ACL | IWSLT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
191–199
Language:
URL:
https://www.aclweb.org/anthology/2020.iwslt-1.24
DOI:
10.18653/v1/2020.iwslt-1.24
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.iwslt-1.24.pdf