We discuss the use of low-dimensional physical models of the voice source for speech coding and processing applications. A class of waveform-adaptive dynamic glottal models and parameter tracking procedures are illustrated. The model and analysis procedures are assessed by addressing speech encoding and enhancement, achievable by using a state space version of the dynamical model in a Extended Kalman filtering framework. The proposed method is shown to provide better SNR improvement if compared to a standard AR Kalman filtering scheme.
Bibliographic reference. Drioli, Carlo / Calanca, Andrea (2011): "Voice processing by dynamic glottal models with applications to speech enhancement", In INTERSPEECH-2011, 1789-1792.