A dynamical system approach to approach to continuous recognition
Vassilios Digalakis, Jan Robin Rohlicek, Mari Ostendorf · 1991
A dynamical system model is proposed for better representing the spectral dynamics of speech for recognition. We assume that the observed feature vectors of a phone segment are the output of a stochastic linear dynamical system and consider two alternative assumptions regarding the relationship of the segment length and the evolution of the dynamics. Training is equivalent to the identification of a stochastic linear system, and we follow a nontraditional approach based on the Estimate-Maximize algorithm. We evaluate this model on a phoneme classification task using the TIMIT database.