5th International Conference on Spoken Language Processing

Sydney, Australia
November 30 - December 4, 1998

Stochastic Calculus, Non-Linear Filtering, and the Internal Model Principle: Implications for Articulatory Speech Recognition

Gordon Ramsay

ICP-INPG, France

A stochastic approach to modelling speech production and perception is discussed, based on Ito calculus. Speech is modelled by a system of non-linear stochastic differential equations evolving on a finite-dimensional state space, representing a partially-observed Markov process. The optimal non-linear filtering equations for the model are stated, and shown to exhibit a predictor-corrector structure, which mimics the structure of the original system. This is used to suggest a possible justification for the hypothesis that speakers and listeners make use of an ``internal model'' in producing and perceiving speech, and leads to a useful statistical framework for articulatory speech recognition.

Full Paper

Bibliographic reference.  Ramsay, Gordon (1998): "Stochastic calculus, non-linear filtering, and the internal model principle: implications for articulatory speech recognition", In ICSLP-1998, paper 0671.