Robust Translation of French Live Speech Transcripts

Elise Bertin-Lemée, Guillaume Klein, Josep Crego, Jean Senellart


Abstract
Despite a narrowed performance gap with direct approaches, cascade solutions, involving automatic speech recognition (ASR) and machine translation (MT) are still largely employed in speech translation (ST). Direct approaches employing a single model to translate the input speech signal suffer from the critical bottleneck of data scarcity. In addition, multiple industry applications display speech transcripts alongside translations, making cascade approaches more realistic and practical. In the context of cascaded simultaneous ST, we propose several solutions to adapt a neural MT network to take as input the transcripts output by an ASR system. Adaptation is achieved by enriching speech transcripts and MT data sets so that they more closely resemble each other, thereby improving the system robustness to error propagation and enhancing result legibility for humans. We address aspects such as sentence boundaries, capitalisation, punctuation, hesitations, repetitions, homophones, etc. while taking into account the low latency requirement of simultaneous ST systems.
Anthology ID:
2022.amta-upg.32
Volume:
Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)
Month:
September
Year:
2022
Address:
Orlando, USA
Editors:
Janice Campbell, Stephen Larocca, Jay Marciano, Konstantin Savenkov, Alex Yanishevsky
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
455–464
Language:
URL:
https://aclanthology.org/2022.amta-upg.32
DOI:
Bibkey:
Cite (ACL):
Elise Bertin-Lemée, Guillaume Klein, Josep Crego, and Jean Senellart. 2022. Robust Translation of French Live Speech Transcripts. In Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track), pages 455–464, Orlando, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Robust Translation of French Live Speech Transcripts (Bertin-Lemée et al., AMTA 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.amta-upg.32.pdf
Data
Europarl-ST