Alimohad, Abdennour, Bouridane, Ahmed and Guessoum, Abderrezak (2014) Efficient Invariant Features for Sensor Variability Compensation in Speaker Recognition. Sensors, 14 (10). pp. 19007-19022. ISSN 1424-8220
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Abstract
In this paper, we investigate the use of invariant features for speaker recognition. Owing to their characteristics, these features are introduced to cope with the difficult and challenging problem of sensor variability and the source of performance degradation inherent in speaker recognition systems. Our experiments show: (1) the effectiveness of these features in match cases; (2) the benefit of combining these features with the mel frequency cepstral coefficients to exploit their discrimination power under uncontrolled conditions (mismatch cases). Consequently, the proposed invariant features result in a performance improvement as demonstrated by a reduction in the equal error rate and the minimum decision cost function compared to the GMM-UBM speaker recognition systems based on MFCC features.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | speaker recognition, invariant features, MFCCs, GMM-UBM, sensor variability, DET curve |
| Subjects: | G400 Computer Science |
| Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
| Depositing User: | Becky Skoyles |
| Date Deposited: | 21 Oct 2014 07:35 |
| Last Modified: | 17 Dec 2023 15:33 |
| URI: | https://nrl.northumbria.ac.uk/id/eprint/17754 |
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