The SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion

Kyle Gorman, Lucas F.E. Ashby, Aaron Goyzueta, Arya McCarthy, Shijie Wu, Daniel You


Abstract
We describe the design and findings of the SIGMORPHON 2020 shared task on multilingual grapheme-to-phoneme conversion. Participants were asked to submit systems which take in a sequence of graphemes in a given language as input, then output a sequence of phonemes representing the pronunciation of that grapheme sequence. Nine teams submitted a total of 23 systems, at best achieving a 18% relative reduction in word error rate (macro-averaged over languages), versus strong neural sequence-to-sequence baselines. To facilitate error analysis, we publicly release the complete outputs for all systems—a first for the SIGMORPHON workshop.
Anthology ID:
2020.sigmorphon-1.2
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:
40–50
Language:
URL:
https://www.aclweb.org/anthology/2020.sigmorphon-1.2
DOI:
10.18653/v1/2020.sigmorphon-1.2
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.sigmorphon-1.2.pdf
Video:
 http://slideslive.com/38929871