By Bertrand Rivet, Jonathon Chambers (auth.), Jordi Solé-Casals, Vladimir Zaiats (eds.)
This quantity comprises the complaints of NOLISP 2009, an ISCA instructional and Workshop on Non-Linear Speech Processing held on the college of Vic (- talonia, Spain) in the course of June 25-27, 2009. NOLISP2009wasprecededbythreeeditionsofthisbiannualeventheld2003 in Le Croisic (France), 2005 in Barcelona, and 2007 in Paris. the most concept of NOLISP workshops is to provide and talk about new principles, ideas and effects regarding replacement techniques in speech processing which may go away from the mainstream. to be able to paintings on the front-end of the topic region, the next domain names of curiosity were de?ned for NOLISP 2009: 1. Non-linear approximation and estimation 2. Non-linear oscillators and predictors three. Higher-order data four. autonomous part research five. Nearest buddies 6. Neural networks 7. determination timber eight. Non-parametric versions nine. Dynamics for non-linear structures 10. Fractal tools eleven. Chaos modeling 12. Non-linear di?erential equations The initiative to arrange NOLISP 2009 on the college of Vic (UVic) got here from the UVic examine crew on sign Processing and used to be supported through the Hardware-Software learn team. we want to recognize the ?nancial aid bought from the M- istry of technology and Innovation of Spain (MICINN), college of Vic, ISCA, and EURASIP. All contributions to this quantity are unique. They have been topic to a doub- blind refereeing process ahead of their reputation for the workshop and have been revised after being awarded at NOLISP 2009.
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Additional info for Advances in Nonlinear Speech Processing: International Conference on Nonlinear Speech Processing, NOLISP 2009, Vic, Spain, June 25-27. Revised Selected Papers
147–154 (2000) 29. : Significance of group delay functions in spectrum estimation. IEEE Trans. Signal Process. 40(9) (1992) Some Experiments in Audio-Visual Speech Processing G. Chollet1 , R. Landais1 , T. Hueber1,2 , H. Bredin1 , C. Mokbel4 , P. Perrot1,3, and L. Zouari1 1 CNRS LTCI/TSI Paris, 46 rue Barrault, 75634 Paris Cedex 13 - France Laboratoire d’Electronique - ESPCI - 10 rue Vauquelin - 75005 Paris - France Institut de Recherche Criminelle de la Gendarmerie Nationale (IRCGN), 93110, Rosny sous bois, France 4 University of Balamand, Po Box 100, Tripoli, Lebanon 2 3 Abstract.
NfPCA ] respectively. Pairwise matching is performed between each Ek and Ekλ , that is between faces directly. As these features treat faces as a whole, location information is lost and the G matrix is reduced to its description part: Gij = f (Cij ). These Cij elements are computed between Ei and Ejλ . This diﬀers with SIFT matching since a single authentication score will be obtained for each test: S(V , V λ ) = M (E , E λ ) . NfP CA ] . 4. The f function is linear for global matching and exponential for local matching.
The form of f function has been chosen by cross-validation between groups G1 and G2 of the BANCA database. Speaker veriﬁcation. 1) of each speaker included in the BANCA database. To overcome the lack of training data dedicated to each speaker, adaptation of a world (or universal) model is performed using the MAP algorithm. The veriﬁcation score is computed as the following likelihood ratio : S(V , V λ ) = 1 Nx log x P (x |λ) P (x |Ω) where x denotes an observation vector in the audio stream of V , Ω the world model and Nx the number of observation vectors considered in the whole speech sequence.