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An Improved Automatic Syllabification Rules for BODO Language

Syllabification acts as a backbone for the unit selection based text-to-speech systems. But with varying language structures the syllabification rules also varies with language. An attempt is made here for improving automatic syllabification rules for BODO language by the addition of extra rules to the current existing rules and implementing it into an algorithm which can be later incorporated into a text-to-speech system. An analysis on the algorithm using 5000 phonetically rich words reveals to yield a comparable result of 99% accuracy as compared to manual syllabification.