Continuous speech recognition on the bases of vector field model for segmentation and feature extraction, and continuous dynamic programming for pattern matching

Abstract

A new model called Vector Field Model is proposed for providing new algorithms of both segmentation and feature extraction in order to recognize phonemic units in continuous speech spoken by many speakers. The original vector field is obtained by differentiating a time-frequency pattern (the output of band-pass filters). In order to extract steady , increasing transient or decreasing transient feature of the point on the time-frequency pattern, three auxiliary vector fields are created by characterizing coherent orientations of vectors. The crowded vectors in an arbitary auxiliary vector field produce a pseudo-phonemic segment. Recognition of /VCV/ is carried out by applying so-called Continuous Dynamic Programming to a segment sequence pattern.