Muralishankar, R and Shrikanth, R and Ramakrishnan, AG (2003) Subspace and Hypothesis based Effective Segmentation of Co-articulated Basic-Units for Concatenative Speech Synthesis. In: Conference on Convergent Technologies for the Asia-Pacific Region: IEEE TENCON 2003., Oct. 14-17, Bangalore, Vol.1 388-392.
In this paper, we present two new methods for Vowel-Consonant segmentation of a co-articulated basic-units employed in our Thirukkural Tamil Text-to-Speech synthesis system . The basic-units considered in  are CV, VC, VCV, VCCV and VCCC, where C stands for a consonant and V for any vowel. In the first method, we use subspace-based approach for vowel-consonant segmentation. It uses oriented principal component analysis (OPCA) where the test feature vectors are projected on to the V and C subspaces. The crossover of the norm-contours obtained by projecting test basic-unit onto the V and C subspaces give the segmentation points which in turn helps in identifying the V and C durations of a test basic-unit. In the second method, we use probabilistic principal component analysis (PPCA)  to get probability models for V and C. We then use Neymen-Pearson (NP) test to segment the basic-unit into V and C. Finally, we show that the hypothesis testing turns out to be an energy detector for V-C segmentation which is similar to the first method.
|Item Type:||Conference Paper|
|Additional Information:||©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Department/Centre:||Division of Electrical Sciences > Electrical Engineering|
|Date Deposited:||25 Aug 2008|
|Last Modified:||19 Sep 2010 04:13|
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