Long-Term Flexible 2D Cepstral Modeling of Speech Spectral Amplitudes
Résumé
This paper presents a method for modeling the envelope of spectral amplitude parameters of speech signals in "two dimensions" (2D). It consists of two cascaded modelings: the first one along the frequency axis is the usual cepstrum technique, which consists of modeling the log-scaled spectral envelope with a Discrete Cosine Model (DCM). The second one, along the time axis, consists of modeling the trajectory of the envelope DCM coefficients by another similar DCM model. An iterative algorithm is proposed to optimally fit this 2D-model to the data according to a perceptual criterion based on frequency masking. This approach is shown to provide an efficient and flexible representation of spectral amplitude parameters in terms of coefficient rates, while providing good signal quality, opening new perspectives in very-low bit-rate sinusoidal speech coding.