By Haizhou Li, Kar-Ann Toh, Liyuan Li
Biometrics is the learn of equipment for uniquely spotting people in accordance with a number of intrinsic actual or behavioral characteristics. After many years of study actions, biometrics, as a famous clinical self-discipline, has complicated significantly either in useful expertise and theoretical discovery to fulfill the expanding want of biometric deployments. during this e-book, the editors supply either a concise and obtainable advent to the sphere in addition to an in depth insurance at the distinctive study issues of their options in a large spectrum of biometrics study starting from voice, face, fingerprint, iris, handwriting, human habit to multimodal biometrics. The contributions additionally current the pioneering efforts and state of the art effects, with specified concentrate on sensible concerns referring to method improvement. This ebook is a invaluable reference for validated researchers and it additionally supplies an outstanding advent for newcomers to appreciate the demanding situations.
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Additional resources for Advanced Topics In Biometrics
A separate oﬀ-glide landmark is thus assigned to a time near the end of the sound. This event is marked [+glide], and is assigned articulator-bound features associated with the oﬀ-glide. Glides are produced with an intermediate narrowing of the vocal tract, so that there are no abrupt discontinuities from an adjacent vowel. Glide landmarks are chosen at times where the signal amplitude becomes a minimum (Sun, 1996). The [+glide] feature is marked for those times. Consonants are produced with an extreme narrowing or complete closing of the vocal tract, resulting in abrupt changes in the signal when the vocal tract closes (closure) and opens (release).
Campbell, J. , Reynolds, D. , and Dunn, R. B. Fusing high- and low- features for speaker recognition, in Proc. Eurospeech, pp. 2665–2668, 2003. , and Vair, C. Compensation of nuisance factors for speaker and language recognition, IEEE Trans. Audio, Speech, and Language Processing 15, 7, 1969–1978, 2007. 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.
2007). 4 Feature transformation (FT) with MAP estimation In the previous section, it has been shown that the feature transforms, which project the speaker-independent features to speaker-dependent features, can be used to characterize speakers. Such transformation matrices are estimated based on the ML criterion. In ML estimation, we assume the parameters are ﬁxed but unknown without any prior knowledge; instead, in MAP estimation, we assume the parameters belong to some prior PDFs, which have been proved as an eﬀective way in dealing with sparse training data.