Teerawee Sukanchanon

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2024

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Leveraging Deep Learning to Shed Light on Tones of an Endangered Language: A Case Study of Moklen
Sireemas Maspong | Francesco Burroni | Teerawee Sukanchanon | Warunsiri Pornpottanamas | Pittayawat Pittayaporn
Proceedings of the Third Workshop on NLP Applications to Field Linguistics

Moklen, a tonal Austronesian language spoken in Thailand, exhibits two tones with unbalanced distributions. We employed machine learning techniques for time-series classification to investigate its acoustic properties. Our analysis reveals that a synergy between pitch and vowel quality is crucial for tone distinction, as the model trained with these features achieved the highest accuracy.
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