This paper presents an approach that uses articulatory features (AFs) derived from spectral features for telephone-based speaker verification. To minimize the acoustic mismatch caused by different handsets, handset-specific normalization is applied to the spectral features before the AFs are extracted. Experimental results based on 150 speakers using 10 different handsets show that AFs contain useful speaker-specific information for speaker verification and the use of handset-specific normalization significantly lowers the error rates under the handset mismatched conditions. Results also demonstrate that fusing the scores obtained from an AF-based system with those obtained from a spectral feature-based (MFCC) system helps lower the error rates of the individual systems.
|ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
|Published - Jan 1 2004
|Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: May 17 2004 → May 21 2004
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering