AlloVera: A Multilingual Allophone Database

David R. Mortensen, Xinjian Li, Patrick Littell, Alexis Michaud, Shruti Rijhwani, Antonios Anastasopoulos, Alan W Black, Florian Metze, Graham Neubig


Abstract
We introduce a new resource, AlloVera, which provides mappings from 218 allophones to phonemes for 14 languages. Phonemes are contrastive phonological units, and allophones are their various concrete realizations, which are predictable from phonological context. While phonemic representations are language specific, phonetic representations (stated in terms of (allo)phones) are much closer to a universal (language-independent) transcription. AlloVera allows the training of speech recognition models that output phonetic transcriptions in the International Phonetic Alphabet (IPA), regardless of the input language. We show that a “universal” allophone model, Allosaurus, built with AlloVera, outperforms “universal” phonemic models and language-specific models on a speech-transcription task. We explore the implications of this technology (and related technologies) for the documentation of endangered and minority languages. We further explore other applications for which AlloVera will be suitable as it grows, including phonological typology.
Anthology ID:
2020.lrec-1.656
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
5329–5336
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.656
DOI:
Bibkey:
Cite (ACL):
David R. Mortensen, Xinjian Li, Patrick Littell, Alexis Michaud, Shruti Rijhwani, Antonios Anastasopoulos, Alan W Black, Florian Metze, and Graham Neubig. 2020. AlloVera: A Multilingual Allophone Database. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5329–5336, Marseille, France. European Language Resources Association.
Cite (Informal):
AlloVera: A Multilingual Allophone Database (Mortensen et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.656.pdf