Voice Processing by Dynamic Glottal Models with Applications to Speech Enhancement

نویسندگان

  • Carlo Drioli
  • Andrea Calanca
چکیده

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.

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تاریخ انتشار 2011