Lexical Tone Recognition in Mizo using Acoustic-Prosodic Features

Parismita Gogoi, Abhishek Dey, Wendy Lalhminghlui, Priyankoo Sarmah, S R Mahadeva Prasanna

Abstract
Mizo is an under-studied Tibeto-Burman tonal language of the North-East India. Preliminary research findings have confirmed that four distinct tones of Mizo (High, Low, Rising and Falling) appear in the language. In this work, an attempt is made to automatically recognize four phonological tones in Mizo distinctively using acoustic-prosodic parameters as features. Six features computed from Fundamental Frequency (F0) contours are considered and two classifier models based on Support Vector Machine (SVM) & Deep Neural Network (DNN) are implemented for automatic tonerecognition task respectively. The Mizo database consists of 31950 iterations of the four Mizo tones, collected from 19 speakers using trisyllabic phrases. A four-way classification of tones is attempted with a balanced (equal number of iterations per tone category) dataset for each tone of Mizo. it is observed that the DNN based classifier shows comparable performance in correctly recognizing four phonological Mizo tones as of the SVM based classifier.
Anthology ID:
2020.lrec-1.795
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6458–6461
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.795
DOI:
Bibkey:
Cite (ACL):
Parismita Gogoi, Abhishek Dey, Wendy Lalhminghlui, Priyankoo Sarmah, and S R Mahadeva Prasanna. 2020. Lexical Tone Recognition in Mizo using Acoustic-Prosodic Features. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6458–6461, Marseille, France. European Language Resources Association.
Cite (Informal):
Lexical Tone Recognition in Mizo using Acoustic-Prosodic Features (Gogoi et al., LREC 2020)
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https://preview.aclanthology.org/nschneid-patch-2/2020.lrec-1.795.pdf
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