This paper discusses the analysis techniques used to derive the excitation waveform for multipulse coding of speech. A cornputationaliy efficient formulation is derived for both covariance and correlation type analyses. These methods differ in the way block edges are treated. Several methods for pulse amplitude and position determination are given, ranging from a purely sequential one to one which reoptimizes pulse amplitudes at each step. It is shown that the reoptimization scheme has a nested structure that allows a reduction in the computations. An efficient nsethod for pulse position coding is given. This method can essentially achieve the entropy limit for randomly placed pulses. Experimental results are given for typic&t configurations including computational requirements and speech quality assessments.
Most text-independent speaker identification methods to date depend on the use of some distance metric for classification.In this paper we develop the use of probability density function (pdf) estimation for text-independent speaker identification.We compare the performance of two parametric and one non-parametric pdf' estimation methods to one distance classification method that uses the Mahalanobis distance. Under all conditions tested, the pdf estimation methods performed substantially better than the Mahalanobis distance method. The best method is a non-parametric pdf estimation method.
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