Spectral stability based event localizing temporal decomposition

In this paper a new approach to Temporal Decomposition (TD) of speech, called Spectral Stability Based Event Localizing Temporal Decomposition(S^2BEL-TD), is presented. The original method of TD proposed by Atal (1983) is known to have the drawbacks of high computational cost, and the high parameter sensitivity of the number and locations of events. In S^2BEL-TD, the event localization is performed based on a maximum spectral stability criterion. This overcomes the high parameter sensitivity of events of Atal's method. Also, S^2BEL-TD avoids the use of the computationally costly singular value decomposition routine used in the Atal's method, thus resulting in a computationally simpler algorithm for TD. Simulation results show that an average spectral distortion of about 1.5 dB can be achieved with line spectral frequencies as the spectral parameter. It is shown that the temporal pattern of the speech excitation parameters can also be well described using the S^2BEL-TD technique