ON MODELING EVENT FUNCTIONS IN TEMPORAL DE COMPOSITION BASED SPEECH CODING

Temporal Decomposition (TD) is an efficient technique for modeling speech spectral evolution through orthogonalization of the matrix of spectral parameters which reduces the amount of spectral information in TD-based speech coding. We have shown in earlier work that "event" functions can be approximated by fixed-width Gaussian functions with a minor degradation in the reconstructed speech, leading to further bit-rate reduction in such systems. In this paper, through perceptually-based spectral distortion measurement, we show the impact of events shape on the speech quality, and propose a new composite function and discuss its effect on the coder performance using different combinations of spectral parameters in event detection and speech synthesis.