Formulation of Syllable Based Pronunciation Models for Tamil Text-to-Speech Synthesizer

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.