Dockum, Rikker
2017-02-05
<p>This paper examines how contextual variables can explain the significant gap in performance for unsupervised modeling of tones in Tai Khamti [ISO 639-3: kht] spoken in Myanmar. Two corpora were extracted from citation tones and tones in running speech in order to assess the utility and limitations of these methods. Taking native judgments as ground truth, current results show high precision on citation tones, between 0.93 and 1.0, in three of the four expected tonal categories, as well as recall 0.79-0.86 in all four. Tones in sentential contexts showed precision just 0.28-0.62, with recall between 0.21 and 0.63.</p>
https://doi.org/10.5281/zenodo.2575298
oai:zenodo.org:2575298
eng
Zenodo
https://zenodo.org/communities/kra-dai
https://doi.org/10.5281/zenodo.2575297
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
BLS43, 43rd Annual Meeting of the Berkeley Linguistics Society, Berkeley, CA, 3-5 February 2017
phonetics
computational linguistics
Tai languages
Tai Khamti
Kra-Dai languages
language documentation
Computational modeling of tone in language documentation: citation tones vs. running speech in Chindwin Khamti [Slides]
info:eu-repo/semantics/lecture