Optimization of a temporal decomposition model of speech

Abstract

A dynamic programming based optimization strategy for a modified temporal decomposition (TD) model of speech is presented. In previous work with the SBEL-TD algorithm, the event localization was performed based on a spectral stability criteria. Although this approach gave reasonably good results (spectral distortion of about 1.5 dB), there was no assurance on the optimality of event locations. In this present work we have optimized the event localization task using a dynamic programming based optimization strategy. An overlapping buffering technique is also proposed to ensure smooth transitions between consecutive speech parameter blocks. Simulation results show that an improved TD model accuracy in terms of the spectral distortion (0.9 dB) can be achieved. The new optimised algorithm also adds a new degree of freedom, TD resolution (events/sec), to the analysis paradigm which can be effectively used to control the TD model accuracy.