Automatic syllable segmentation of Myanmar texts using finite state transducer

Automatic syllabification lies at the heart of script processing especially for the South East Asian scripts like Myanmar. Myanmar syllabification algorithms implemented so far are either rule-based or dictionary-based approach. This paper proposes a new method for Myanmar syllabification which deploys formal grammar and un-weighted finite state transducers (FST). Our proposed method focuses on orthographic way of syllabification for the input texts encoded in Unicode. We tackle syllabification of Myanmar words with standard syllable structure as well as words with irregular structures such as kinzi, consonant stacking which have not been resolved by previous methods. Our FST based syllabifier was tested on 11,732 distinct words contained in Myanmar Orthography Corpus. These words yielded 32,238 syllables and are compared with correctly hand syllabified words. Our FST based syllabification method performs with99.93% accuracy on Stuttgart FST (SFST) tools. DOI: http://dx.doi.org/10.4038/icter.v6i2.7150 International Journal on Advances in ICT for Emerging Regions (ICTer), 2013;v.6(2