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Tamil Talk: What you speak is what you get!

Ogunshile, Emmanuel; Ramachandran, Raj

Authors

Profile image of Emmanuel Ogunshile

Dr Emmanuel Ogunshile Emmanuel.Ogunshile@uwe.ac.uk
Programme Leader for BSc(Hons) Data Science & PhD Director of Studies



Contributors

David Mann
Researcher

Kim Frederic
Researcher

Naomi Weston
Researcher

Abstract

Tamil is one of the longest surviving classical languages in the world. Speech to text in Tamil would benefit to
a lot of native Tamil speakers throughout the world. There are many speech recognition and speech to text applications
available for a wide variety of languages but many minority languages, such as Tamil are overlooked. In this paper, we
propose to develop a system for Tamil speech to text that will be consitent with the pronunciation of the user and conforms wih the syntax of the language.

Presentation Conference Type Conference Paper (unpublished)
Conference Name CONISOFT 2019 : IEEE 7th International Conference on Software Engineering Research and Innovation
Start Date Oct 23, 2019
End Date Oct 25, 2019
Deposit Date Aug 23, 2019
Publicly Available Date Aug 30, 2019
Keywords Speech to text, Application, Agile, Tamil Language, Tamil Orthography, Speech Recognition, ASR
Public URL https://uwe-repository.worktribe.com/output/2419491
Publisher URL http://conisoft.org/2019