Stochastic model of diphone-like segments based on trajectory concepts

A new global approach to coarse classification of speech segments is presented. Markov modeling is applied on an analytic approach to coarticulation. Speech signal evolution of diphone-like segments is modelized by a point moving frame by frame in a factorial space. Kinematic segmentation applied to the trajectory covered by this point enables the authors to build stochastic models of these segments. Input parameters of a Markov model are extracted from a skeleton of this trajectory considered as a functional model of overlapping segments. The evaluation of such representations in a recognition task gives some elements of discussion about the relative information contained in steady states versus transient segments and acoustical trajectories in general