A parser for segmenting continuous speech into pseudo-syllabic nuclei

A parser for segmenting continuous speech into pseudo-syllabic nuclei is presented. It uses an Augmented Transition Network Grammar whose rules relate a minimum set of phonetic features useful for segmentation with acoustic features extracted from the speech spectra. Possible ambiguities are dealt with by assigning degrees of worthiness to the rules as well as to the acoustic features extracted from the speech spectra. The parser gives single syllabic hypotheses with non-fuzzy bounds when the input data are enough evident and lattices of syllabic hypotheses with well defined bounds when the input data are not enough precise.