Grapheme-to-Phoneme Conversion with a Multilingual Transformer Model

Omnia ElSaadany, Benjamin Suter


Abstract
In this paper, we describe our three submissions to the SIGMORPHON 2020 shared task 1 on grapheme-to-phoneme conversion for 15 languages. We experimented with a single multilingual transformer model. We observed that the multilingual model achieves results on par with our separately trained monolingual models and is even able to avoid a few of the errors made by the monolingual models.
Anthology ID:
2020.sigmorphon-1.7
Volume:
Proceedings of the 17th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
Month:
July
Year:
2020
Address:
Online
Venues:
ACL | SIGMORPHON | WS
SIG:
SIGMORPHON
Publisher:
Association for Computational Linguistics
Note:
Pages:
85–89
URL:
https://www.aclweb.org/anthology/2020.sigmorphon-1.7
DOI:
Bib Export formats:
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PDF:
https://www.aclweb.org/anthology/2020.sigmorphon-1.7.pdf

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