A Deep Generative Model of Vowel Formant Typology

Ryan Cotterell, Jason Eisner


Abstract
What makes some types of languages more probable than others? For instance, we know that almost all spoken languages contain the vowel phoneme /i/; why should that be? The field of linguistic typology seeks to answer these questions and, thereby, divine the mechanisms that underlie human language. In our work, we tackle the problem of vowel system typology, i.e., we propose a generative probability model of which vowels a language contains. In contrast to previous work, we work directly with the acoustic information—the first two formant values—rather than modeling discrete sets of symbols from the international phonetic alphabet. We develop a novel generative probability model and report results on over 200 languages.
Anthology ID:
N18-1004
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
37–46
Language:
URL:
https://www.aclweb.org/anthology/N18-1004
DOI:
10.18653/v1/N18-1004
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PDF:
http://aclanthology.lst.uni-saarland.de/N18-1004.pdf
Video:
 http://vimeo.com/276386708