Semi-automatic syllable-like segmentation for Hindi

The goal of this study is automatic segmentation of speech at syllable level and also that the reasonable number of syllables may suffice the need for travel domain applications. This paper presents study of algorithm for identifying syllables based on linguistic rules in Hindi words. After survey of the relevant literature, a set of rules are identified and implemented as a simple easy-to-implement algorithm. The algorithm is tested on 2400 distinct words and algorithm performs with 99.5% accuracy for segmentation of written text. A baseline group delay based segmentation technique is applied on spoken speech sentences to generate labeled database at syllable level. The system is validated against a few manually segmented speech utterances. It is observed that vowels are more accurately segmented as compared to fricatives. It is seen that nearly accurate segmentation is achieved if the window scale factor is modified for each sentence.