Robust cepstral featurefs for speaker identification

Khded T. Assdeh, Richard J. Mammone

Research output: Contribution to journalConference article

9 Scopus citations

Abstract

In this paper we introduce a new set of features that provides improved performance for speaker identification. This feature set is referred to as the adaptive component weighting (ACW) cep stral coefficients. The ACW scheme modifies the linear predictive (LP) spectral components (resonances) so as to emphasize the formant structure by attenuating the broad-bandwidth spectral components. Such components are found to introduce undesired variability in the LP spectra of speech signals due to environmental factors. The ACW cepstral coefficients represent an adaptively weighted version of the LP cepstrum. The adaptation results in deemphasising the irrelevant variations of the LP cepstral coefficients on a frame-by-frame basis. Experiments are presented using the San Diego portion of the King database. The ACW cepstrum is shown to offer improved speaker identification performance as compared to other common methods of cepstral weighting.

Original languageEnglish (US)
Article number389338
Pages (from-to)I1293-I132
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume1
DOIs
StatePublished - Jan 1 1994
EventProceedings of the 1994 IEEE International Conference on Acoustics, Speech and Signal Processing. Part 2 (of 6) - Adelaide, Aust
Duration: Apr 19 1994Apr 22 1994

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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