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Improving SVF with DISTBIC for Phoneme Segmentation

Abstract : In this paper we examine an application for phoneme segmentation of DISTBIC, a two-pass, textindependent method traditionally used for speaker segmentation. The novelty of this paper is its experimentation with use of the spectral variation function (SVF), a simple non-parametric method for phone segmentation, as a replacement for the distance measure of the first pass of DISTBIC. In doing so we aim to produce a computationally efficient method for text-independent phoneme segmentation that provides good performance. Experiments are carried out on the TIMIT database. We give a performance comparison between the SVF as previously used for segmentation, our DISTBIC-SVF algorithm, and another state-of-the-art algorithm.
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Submitted on : Sunday, December 4, 2011 - 3:49:21 PM
Last modification on : Thursday, January 20, 2022 - 5:26:33 PM
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  • HAL Id : hal-00647985, version 1



Joshua Winebarger, Khalid Daoudi, Hussein yahia. Improving SVF with DISTBIC for Phoneme Segmentation. International Conference Speech and Computer (SPECOM), Sep 2011, Kazan, Russia. ⟨hal-00647985⟩



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