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Sequence Kernels for Speaker and SpeechRecognition Mark Gales - ...
mi.eng.cam.ac.uk/~mjfg/jhu09.pdf16 Jul 2009: a:a/1. b:b/1. a:a/1. b:b/1. a: /1ε. b: /1ε. a: /1ε. b: /1ε. ... a22. 23. 44. 45. oo1. b b3 4()()b2. 1. (). (a) Standard HMM phone topology. -
Uniform precision ultrasound strain imaging G.M. Treece, J.E. Lindop, …
mi.eng.cam.ac.uk/reports/svr-ftp/treece_tr624.pdf9 Mar 2009: b) B-mode image of a breast invasive carcinoma withsurrounding ductal carcinoma in situ, (d) strain image using Gaussian filtering and (f) using C1NPR. ... b) B-mode image showingscrotal calcification, (d) strain image using Gaussian filtering and (f) -
MULTIPLE KERNEL LEARNING FOR SPEAKER VERIFICATION C. Longworth and ...
mi.eng.cam.ac.uk/~mjfg/cl336_ICASSP08.pdf2 Mar 2009: weighted sum of the individual kernels.q W WsrmB I :t B q B W < (6). ... B @ D OR @ D u p @ D %. @ D uw P: t Buw > rmB I :t B. -
IEEE TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING, VOL. ...
mi.eng.cam.ac.uk/~mjfg/cl336_ASP09.pdf2 Mar 2009: B. Derivative Kernels. Derivative kernels provide an interesting contrast to para-metric kernels. ... N (s), wk = {w. (1)k ,. , w. (S)k }, b = {b.
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