Interpolation of lost speech segments using LP-HNM model with codebook-mapping post-processing

This paper presents a method for interpolation of lost speech segments. The short-time spectral amplitude (STSA) of speech is modeled using a linear prediction (LP) model of the spectral envelop and a harmonic plus noise model (HNM) of the excitation. The restoration algorithm is based on interpolation of the parameters of LP-HNM models of speech from both side of the gap. A codebook mapping (CBM) technique is used to fit the interpolated parameters to a pre-trained speech model. Experiments show that the CBM module mitigates the artifacts that may result from interpolation of relatively long speech gaps. Evaluations demonstrate that the proposed interpolation method results in a superior quality in comparison to alternative restoration methods.