Particle Filter Inference in an Articulatory-Based Speech Model

A speech model parameterized by formant frequencies, formant bandwidths, and formant gains is proposed. Inference in the model is made by particle filtering for the application of speech enhancement. The advantage of the proposed parameterization over existing parameterizations based on auto-regressive (AR) coefficients or reflection coefficients is the smooth time-varying behavior of the parameters and their loose coupling. Experiments confirm this advantage both in terms of parameter estimation and SNR improvement.