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TRAINING AND ADAPTING MLP FEATURES FOR ARABIC SPEECH RECOGNITION
mi.eng.cam.ac.uk/research/projects/AGILE/publications/park_icassp09.pdf7 Oct 2009: 4. NETWORK ADAPTATION. The standard approach for speaker adaptation when using MLP fea-tures is simply to use the same form of adaptation applied, for exam-ple, to PLP-based systems. -
paper.2col.dvi
mi.eng.cam.ac.uk/~mjfg/kai_ASP09.pdf2 Mar 2009: This will be referred to as acriterion mapping function(CMF). The specific form exam-ined in this work is to map a speaker-specific ML-estimatedlinear transform to be more similar -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2009-CVPR-hand-trackingpdf28 Jul 2009: Figures10 and11 show exam-ples on the face dataset. 5. Summary and Conclusion. -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2009-CVPR-hand-trackerpdf.pdf28 Jul 2009: Figures10 and11 show exam-ples on the face dataset. 5. Summary and Conclusion. -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2009-CVPR-hand-trackingpdf.pdf28 Jul 2009: Figures10 and11 show exam-ples on the face dataset. 5. Summary and Conclusion. -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2009-CVPR-hand-trackerpdf.pdf28 Jul 2009: Figures10 and11 show exam-ples on the face dataset. 5. Summary and Conclusion. -
Learning to Track with Multiple Observers Björn StengerComputer…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2009-CVPR-hand-trackingpdf.pdf28 Jul 2009: Figures10 and11 show exam-ples on the face dataset. 5. Summary and Conclusion.
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