Mark Hasegawa-Johnson. Ozgur Cetin. Kate Saenko. November 12, ... UIUC (Hasegawa-Johnson et al.) MIT (Livescu, ... Mark Hasegawa-Johnson, U. Illinois at ...
Kate Saenko. November 12, 2005. Dynamic Bayesian network implementation: ... for acoustic model, using only articulatory 'ground truth' and acoustics ...
smoker. genes. parent smoker. profession. Things we may want to know: ... Is lung cancer independent of profession given that the person is a smoker? ...
For the local evidence, we can use a discriminative classifier (trained iid) ... Uses inference as subroutine (can be slow no worse than discriminative learning) ...
Take advantage of human perception and production knowledge ... Growing number of sites investigating complementary aspects of this idea; a non-exhaustive list: ...
An introduction to Bayesian Networks and the Bayes Net Toolbox for Matlab Kevin Murphy MIT AI Lab 19 May 2003 Outline An introduction to Bayesian networks An overview ...
The Bayes Net Toolbox for Matlab and applications to computer vision Kevin Murphy MIT AI lab Outline of talk BNT Outline of talk BNT Using graphical models for visual ...
A K rnyezetgazd lkod si agr rm rn ki, illetve a Term szetv delmi m rn ki alapk pz si (BSc) szakok k pes t si k vetelm nyeinek kidolgoz sa, a szakok ...
Frame-level accuracies. MLPs trained on Fisher. Accuracy computed with respect to SVB test set ... Silence frames excluded from this calculation. 68.0. ht. 69.2 ...
AR 'knitting' example. unknown: t bqwA. kn.roman: yibqu. ops: ... Knitting local model n-best 30.0% 23.1% (n = 25) Varying the number of dictionary matches ...
Edinburgh: Tested successfully on GridEngine; not yet on Condor. UW: Tested unsuccessfully (?) on music (pmake) cluster & Condor. UIUC: ? JHU: ? Try it at home! ...
... SVitchboard - Small Vocabulary Switchboard. SVitchboard [King, Bartels ... Trained on all of Fisher but not on any data from Switchboard 1. SVitchboard ...