New LP-Derived Features for Speaker Identification

Khaled T. Assaleh, Richard J. Mammone

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

A new set of features is introduced that has been found to improve the performance of automatic speaker identification systems. The new set of features is referred to as the adaptive component weighting (ACW) cepstral coefficients. The new features emphasize the formant structure of the speech spectrum while attenuating the broad-bandwidth spectral components. The attenuated components correspond to the variations in spectral tilt of transmission and recording environment, and other characteristics that are irrelevant to speaker identification. The resulting ACW spectrum introduces zeros into the usual all-pole linear prediction (LP) spectrum. This is equivalent to applying a finite impulse response (FIR) filter that normalizes the narrow band modes of the spectrum. Unlike existing fixed cepstral weighting schemes, the ACW cepstrum provides an adaptively weighted version of the LP cepstrum. The adaptation results in deemphasizing the irrelevant variations of the LP cepstral coefficients on a frame-by-frame basis. The ACW features are evaluated for text-independent speaker identification and are shown to yield improved performance.

Original languageEnglish (US)
Pages (from-to)630-638
Number of pages9
JournalIEEE Transactions on Speech and Audio Processing
Volume2
Issue number4
DOIs
StatePublished - Oct 1994

All Science Journal Classification (ASJC) codes

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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