FORMULATION OF SYLLABLE BASED PRONUNCIATION MODELS FOR TAMIL TEXT-TO-SPEECH SYNTHESIZER

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Vaibhavi Rajendran
G Bharadwaja Kumar

Abstract

The primary aim of Human-Computer Interaction (HCI) is to deliver the power of computers and communication systems to people in an easily accessible and understandable form. HCI in a person’s native/first language is always invigorate.  Developing a Tamil Text-To-Speech (TTS) system will facilitate a convenient medium of interaction for people who speak Tamil language.  This paper emphasizes on the development of pronunciation models, a vital component of a Tamil TTS. Developing a pronunciation model for Tamil is more arduous when compared to other languages due to the non-triviality between the letter to sound correspondence. Veritably, two syllable-based pronunciation models developed by us are discussed in this paper.  First, is a syllable-centric rule-based pronunciation model that generates a well-founded training data which is ingrained into the second, Conditional Random Field (CRF) enforced model.  It is evident that both of  these models are dominions  with a high Mean Similarity Score of 0.97 and 0.94 respectively in comparison to the other existing rule driven and data driven models in the literature. These syllable-based pronunciation models will enrich the performance of a Tamil TTS.

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How to Cite
Rajendran, V., & Kumar, G. B. (2020). FORMULATION OF SYLLABLE BASED PRONUNCIATION MODELS FOR TAMIL TEXT-TO-SPEECH SYNTHESIZER. Malaysian Journal of Computer Science, 33(4), 282–297. https://doi.org/10.22452/mjcs.vol33no4.3
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