Abstract
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 language | English |
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Pages (from-to) | IV/4160 |
Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Volume | 4 |
State | Published - 2002 |
Event | 2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States Duration: May 13 2002 → May 17 2002 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering