By Haizhou Li, Kar-Ann Toh, Liyuan Li
Biometrics is the examine of tools for uniquely spotting people in response to a number of intrinsic actual or behavioral qualities. After a long time of study actions, biometrics, as a well-known medical self-discipline, has complex significantly either in sensible expertise and theoretical discovery to fulfill the expanding want of biometric deployments. during this ebook, the editors offer either a concise and available advent to the sector in addition to an in depth assurance at the designated examine issues of their strategies in a large spectrum of biometrics learn starting from voice, face, fingerprint, iris, handwriting, human habit to multimodal biometrics. The contributions additionally current the pioneering efforts and cutting-edge effects, with certain specialise in sensible matters touching on procedure improvement. This publication is a helpful reference for proven researchers and it additionally offers a very good creation for newbies to appreciate the demanding situations.
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J. and Woodland, P. C. Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models, Computer Speech and Language 9, 171–185, 1995. , Lee, K. , Sim, K. , and Jin, Q. The 14U system in NIST 2008 speaker recognition evaluation, in Proc. ICASSP, pp. 4201–4204, 2009. Li, K. P. and Porter, J. E. Normalizations and selection of speech segments for speaker recognition scoring, in Proc. ICASSP, pp. 1:595–598, 1988. , and Dai, L. Exploiting prosodic information for speaker recognition, in Proc.
The recent progress features the use of high-dimensional feature vectors, which are also called supervectors (Kinnunen and Li, 2010). It should be noted that the compensation of the session variability plays a critical role in system design. With the invention of JFA and NAP, the speaker recognition performance in mismatched acoustic environments has been greatly enhanced. Despite much success, many challenges remain ahead of us. The performance gap between the text-independent speaker recognition and text-dependent speaker recognition is still large.
Che, C. , and Yuk, D. S. An HMM approach to text-prompted speaker verification, in Proc. ICASSP, pp. 673–676, 1996. Davis, S. and Mermelstein, P. Comparison of parametric representation for monosyllabic word recognition in continuous spoken sentence, IEEE Trans. Acoustic and Speech Signal Processing 28, 357–366, 1980. , and Neumeyer, L. G. Speaker adaptation using constrained estimation of Gaussian mixtures, IEEE Trans. Speech and Audio Processing 3, 5, 357–366, 1995. Doddington, G. Speaker recognition based on idiolectal differences between speakers, in Proc.