A unified parser for developing Indian language text to speech synthesizers

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Abstract

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.

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APA

Baby, A., Nishanthi, N. L., Thomas, A. L., & Murthy, H. A. (2016). A unified parser for developing Indian language text to speech synthesizers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9924 LNCS, pp. 514–521). Springer Verlag. https://doi.org/10.1007/978-3-319-45510-5_59

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