This paper reports a preliminary attempt on data-driven modeling of segmental (phoneme) duration for two Indian languages Hindi and Telugu. Classification and Regression Tree (CART) based data-driven duration modeling for segmental duration prediction is presented. A number of features are proposed and their usefulness and relative contribution in segmental duration prediction is assessed. Objective evaluation of the duration models, by root mean squared prediction error (RMSE) and correlation between actual and predicted durations, is performed. The duration models developed have been implemented in an Indian language Text-to-Speech synthesis system [1] being developed within Festival framework [2].
Cite as: Krishna, N.S., Murthy, H.A. (2004) Duration modeling of Indian languages Hindi and Telugu. Proc. 5th ISCA Workshop on Speech Synthesis (SSW 5), 197-202
@inproceedings{krishna04_ssw,
author={N. Sridhar Krishna and Hema A. Murthy},
title={{Duration modeling of Indian languages Hindi and Telugu}},
year=2004,
booktitle={Proc. 5th ISCA Workshop on Speech Synthesis (SSW 5)},
pages={197--202}
}