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.
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Hong, Q., Wang, S., Liu, Z. (2014). A Robust Speaker-Adaptive and Text-Prompted Speaker Verification System. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_43
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DOI: https://doi.org/10.1007/978-3-319-12484-1_43
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
Online ISBN: 978-3-319-12484-1
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