A novel method for blind segmentation of Thai continuous speech

This paper describes an acoustical investigation on Thai speech segmentation using a combination of average level crossing rate (ALCR) and root-mean-square (RMS) energy. Simple and easy to compute, ALCR information alone was successfully used in an automatic speech segmentation system for English. However, ALCR has never been applied to Thai. As a result, the objective of the study is to apply ALCR information to ascertain its usefulness in detecting significant temporal changes in continuous Thai Speech. An experiment was conducted on a small speech corpus containing 21 sentences. Preliminary results suggest that ALCR and RMS energy can be used to detect the phonetic boundary between obstruent initial consonant and preceding/following vowel. In addition, it can also be used to detect boundary between final consonant of the preceding syllable and initial consonant of the following syllable except for the case involving two successive non-identical nasals. The overall accuracy is around 81% for data from four speakers.