Name
Abstract | ||
|---|---|---|
Currently, the recording playback attack has become a major security risk for speaker verification. The text-independent or text-dependent system is being troubled by it. In this paper, we propose an effective text-prompted system to overcome this problem, in which speaker verification and speech recognition are combined together. We further adopt speaker-adaptive hidden Markov model (HMM) so as to improve the verification performance. After HMM-based speaker adaptation, this system needs not to be retrained at each verification step. Experimental results demonstrated that the proposed method had quite good performance with the equal error rate (EER) lower than 2% and was also robust for different cases. |
Year | Venue | Keywords |
|---|---|---|
2014 | BIOMETRIC RECOGNITION (CCBR 2014) | recording playback,speaker verification |
Field | DocType | Volume |
Speaker verification,Computer science,Word error rate,Speech recognition,Hidden Markov model,Replay attack,Speaker adaptation | Conference | 8833 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Q. Y. Hong | 1 | 50 | 15.79 |
| Wang Sheng | 2 | 8 | 5.80 |
| Zhijian Liu | 3 | 59 | 9.80 |