Time-aligned SVD analysis for speaker identification

Patrick Clemins, Heather Ewalt, Michael Johnson

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


This paper presents a time-aligned singular value decomposition (SVD) analysis for speaker identification. SVD analysis has been used for fast spectral matching based on a global representation of an entire utterance. We incorporate temporal normalization directly into the decomposition by using a dynamic time warping (DTW) path to time-align the rows of the feature matrix prior to SVD analysis. Speaker identification results using the TI-46 database indicates that the time-aligned SVD significantly improves accuracy for most threshold choices.

Original languageEnglish
Pages (from-to)IV/4160
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2002
Event2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States
Duration: May 13 2002May 17 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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