The Human–Computer Interaction era contrived the researchers to work on speech and languages to develop interactive interfaces. A speech synthesizer is one such interface facilitating people to amalgamate with the digital era. The present work is focused on developing a Letter-To-Sound mapping for a Tamil speech synthesizer, which is an intriguing task due to the script to sound mapping irregularities in Tamil. Tamil is a syllable-timed language, hence a new syllable centric rule-based approach is formulated in the present work with a more extended set of rules than the existing rule-bases in the literature. This proposed rule-based system outperforms the existing rule-based systems with a low Character Error Rate and High Mean Similarity Score. © 2018, © 2018 IETE.

Bharadwaja Kumar

Computer Science

School of Computer Science and Engineering

Chennai Campus

Vaibhavi Rajendran

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

A Robust Syllable Centric Pronunciation Model for Tamil Text To Speech Synthesizer

IETE Journal of Research

Procedia Computer Science

Multi-label Classification: Problem Transformation methods in Tamil Phoneme classification

Natural Language Engineering

Phonetisaurus: Exploring grapheme-to-phoneme conversion with joint n-gram models in the WFST framework

This paper describes the design of a language independent parser for text-to-speech synthesis in Indian languages. Indian languages come from 5–6 different language families of the world. Most Indian languages have their own scripts. This makes parsing for text to speech systems for Indian languages a difficult task. In spite of the number of different families which leads to divergence, there is a convergence owing to borrowings across language families. Most importantly Indian languages are more or less phonetic and can be considered to consist broadly of about 35–38 consonants and 15–18 vowels. In this paper, an attempt is made to unify the languages based on this broad list of phones. A common label set is defined to represent the various phones in Indian languages. A uniform parser is designed across all the languages capitalising on the syllable structure of Indian languages. The proposed parser converts UTF-8 text to common label set, applies letter-to-sound rules and generates the corresponding phoneme sequences. The parser is tested against the custom-built parsers for multiple Indian languages. The TTS results show that the accuracy of the phoneme sequences generated by the proposed parser is more accurate than that of language specific parsers. © Springer International Publishing Switzerland 2016.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A unified parser for developing Indian language text to speech synthesizers

Indian Journal of Science and Technology

A Hierarchical Approach in Tamil Phoneme Classification using Support Vector Machine

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Grapheme-to-phoneme conversion using Long Short-Term Memory recurrent neural networks

Journal	IETE Journal of Research
Publisher	Informa UK Limited
ISSN	0377-2063
Open Access	0