CLUZH at SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion

Peter Makarov, Simon Clematide


Abstract
This paper describes the submission by the team from the Institute of Computational Linguistics, Zurich University, to the Multilingual Grapheme-to-Phoneme Conversion (G2P) Task of the SIGMORPHON 2020 challenge. The submission adapts our system from the 2018 edition of the SIGMORPHON shared task. Our system is a neural transducer that operates over explicit edit actions and is trained with imitation learning. It is well-suited for morphological string transduction partly because it exploits the fact that the input and output character alphabets overlap. The challenge posed by G2P has been to adapt the model and the training procedure to work with disjoint alphabets. We adapt the model to use substitution edits and train it with a weighted finite-state transducer acting as the expert policy. An ensemble of such models produces competitive results on G2P. Our submission ranks second out of 23 submissions by a total of nine teams.
Anthology ID:
2020.sigmorphon-1.19
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:
171–176
Language:
URL:
https://aclanthology.org/2020.sigmorphon-1.19
DOI:
10.18653/v1/2020.sigmorphon-1.19
Bibkey:
Cite (ACL):
Peter Makarov and Simon Clematide. 2020. CLUZH at SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion. In Proceedings of the 17th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 171–176, Online. Association for Computational Linguistics.
Cite (Informal):
CLUZH at SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion (Makarov & Clematide, SIGMORPHON 2020)
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PDF:
https://preview.aclanthology.org/update-css-js/2020.sigmorphon-1.19.pdf