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

Voice processing by dynamic glottal models with applications to speech enhancement

DRIOLI, Carlo;CALANCA, Andrea
2011

Abstract

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
Speech enhancement; glottal modeling
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/389570
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