Automatic Segmentation of Separately Pronounced Sinhala Words into Syllables

Abstract

Aligned corpora are widely used in various speech applications like automatic speech recognition, speech synthesis, as well as prosodic and phonetic research. The segmentation into syllables can be done manually or automatically. But it consumes significantly more time for a fully manual phonetic segmentation and practically it is a complicated task because in many cases it requires a large aligned speech corpus. If the manual syllabification is done by a group of individuals then the consistency is decreased because the analysis variations of the individuals. Consequently, there is a dire need for automatic syllabification and it is important because Sinhala language is syllable centric in nature. A method for syllabification of acoustic signals of separately pronounced Sinhala words has been given. Detecting the syllable boundaries was achieved by two main phases and those phases have been described with examples. Keywords: