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Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2009-CVPR-hand-trackingpdf.pdf28 Jul 2009: The running of tests consisting of all possible combina-tions of all trackers on all test sequences would take a pro-hibitive amount of time to complete. ... In order to test the validity of such a setup, weperformed tests using the complete tracking -
Model-Based Approaches to Speaker andEnvironment Adaptation Mark…
mi.eng.cam.ac.uk/~mjfg/mjfg_china09.pdf28 Apr 2009: Noisy CMLLR vs CMLLR Performance. • Evaluated on engine-on/highway noise condition from the Toshiba data– phone-numbers task (unknown digit length sequences)– see next section for test data configuration, here ... Noise Parameter Estimation. • In -
report.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/ijaz_tr635.pdf20 Aug 2009: Exploration is the ability to test various regionsin the problem space to reach a global optimum and exploitation is the ability to search aroundthe candidate solution. -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2009-CVPR-hand-trackerpdf.pdf28 Jul 2009: The running of tests consisting of all possible combina-tions of all trackers on all test sequences would take a pro-hibitive amount of time to complete. ... In order to test the validity of such a setup, weperformed tests using the complete tracking -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2009-CVPR-hand-trackingpdf.pdf28 Jul 2009: The running of tests consisting of all possible combina-tions of all trackers on all test sequences would take a pro-hibitive amount of time to complete. ... In order to test the validity of such a setup, weperformed tests using the complete tracking -
MULTIPLE KERNEL LEARNING FOR SPEAKER VERIFICATION C. Longworth and ...
mi.eng.cam.ac.uk/~mjfg/cl336_ICASSP08.pdf2 Mar 2009: 8] A. Martin, “The NIST year 2002 speaker recog-nition evaluation plan,” 2002, Available fromhttp://www.nist.gov/speech/tests/spk/2002/doc. -
A Generalised Derivative Kernel for Speaker Verification C. Longworth …
mi.eng.cam.ac.uk/~mjfg/cl336_INTER08.pdf2 Mar 2009: 15, pp. 2465–2475, 2007. [10] A. Martin, “The NIST year 2002 speaker recog-nition evaluation plan,” 2002, available fromhttp://www.nist.gov/speech/tests/spk/2002/doc. -
icassp09.dvi
mi.eng.cam.ac.uk/research/projects/AGILE/publications/raut-icassp09.pdf21 Jul 2009: As they are not re-estimated on the test data, they are not sensitive to the supervisionhypothesis errors or limited amount of data. ... The test-set eval03 consists of about 6 hours of data from144 speakers, taken from Swbd and Fisher corpora. -
paper_pcw_v1.dvi
mi.eng.cam.ac.uk/research/projects/AGILE/publications/park_interspeech09.pdf7 Oct 2009: MLP config. Training data Train Acc. Test Acc. 1350hr 69.51% 65.61%1350hr big 71.37% 67.57%200hr set #1 68.77% 63.92%200hr set #2 68.54% ... 4.2. Unadapted decoding results. In a first test series the use of MLP features is evaluated withinthe -
Uniform precision ultrasound strain imaging G.M. Treece, J.E. Lindop, …
mi.eng.cam.ac.uk/reports/svr-ftp/treece_tr624.pdf9 Mar 2009: Local strain. 5This data set was previously used to test a parametric method for non-uniform smoothing: see Fig. ... The phantom data in Figs. 4, 5 and 6 was also used to test convergence for various methods ofsolving eq.
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