Abstract
In this paper, hum of a person is used in voice biometric system. In addition, recently proposed feature set, i.e., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC), is found to capture perceptually meaningful source-like information from hum signal. For person recognition, MFCC gives EER of 13.14% and %ID of 64.96%. A reduction in equal error rate (EER) by 0.2% and improvement in identification rate by 7.3 % is achieved when a score-level fusion system is employed by combining evidence from MFCC (system) and VTMFCC (source-like features) than MFCC alone. Results are reported for various feature dimensions and population sizes.
Original language | English (US) |
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Pages (from-to) | 369-372 |
Number of pages | 4 |
Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
State | Published - Dec 1 2011 |
Event | 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy Duration: Aug 27 2011 → Aug 31 2011 |
Keywords
- Fusion of Source-System features
- Humming
- Polynomial classifier
- VTEO
- VTMFCC