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Bitext Alignment forStatistical Machine Translation Yonggang Deng A…
mi.eng.cam.ac.uk/~wjb31/ppubs/YDengDissertationDec05.pdf16 Feb 2008: Bitext Alignment forStatistical Machine Translation. Yonggang Deng. A dissertation submitted to the Johns Hopkins University in conformity with the. requirements for the degree of Doctor of Philosophy. Baltimore, Maryland. 2005. Copyright c 2005 by -
Bitext Alignment for Statistical Machine Translation
mi.eng.cam.ac.uk/~wjb31/ppubs/YDengDefenseDec05.pdf16 Feb 2008: 20. 21. 22. 23. 24. 25. Coverage. eval02eval03eval04. 1 2 3 4 523.2. ... 23.4. 23.6. 23.8. 24. 24.2. 24.4. 24.6. 24.8. 25. 25.2. BLEU. -
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mi.eng.cam.ac.uk/~wjb31/ppubs/VlasiosDoumpiotisDissOct04.pdf16 Feb 2008: "$#&%'(),.-%/01 " 2-3 2 42 56879;:<=1) >?1 01@ " ABC". DE F(GH42IJKC7 #%L88NM :O88 F1@ ". PQSRUTWVYXUT&ZX[1]_VYXCaVYT. -
- + Code Breaking for Automatic Speech ...
mi.eng.cam.ac.uk/~wjb31/ppubs/VenkataramaniThesisTalk05.pdf16 Feb 2008: Code Breaking for Automatic Speech Recognition 24 |35). < > -. Studying Segment Set Pruning. Towards studying the ability of lattice pinching in. -
thesis.dvi
mi.eng.cam.ac.uk/~wjb31/ppubs/VenkataramaniDiss05.pdf16 Feb 2008: 233.3.3 Obtaining Confusions from a Lattice. 24. 3.4 Obtaining Relevant Training data for the Binary Classifiers. -
Minimum Bayes-Risk Techniques forAutomatic Speech Recognition and…
mi.eng.cam.ac.uk/~wjb31/ppubs/SKumarPhDefense2004.pdf16 Feb 2008: Minimum Bayes-Risk Classifiers for Machine Translation. Conclusions and Future Work. MBR Techniques in Automatic Speech Recognition and Machine Translation – p.24/33. -
Minimum Bayes-Risk Techniquesin Automatic Speech Recognition and…
mi.eng.cam.ac.uk/~wjb31/ppubs/ShankarKumarDiss04.pdf16 Feb 2008: 21.9 7.91 0.70 46.46 68.494 24.2 7.56 0.75 47.84 70.265 19.2 7.25 0.72 49.56 71.186 -
Statistical Machine Translationand Automatic Speech Recognitionunder…
mi.eng.cam.ac.uk/~wjb31/ppubs/LMathiasDissDec07.pdf16 Feb 2008: 232.8.4 Phrase Extraction from a Lattice. 24. 2.9 ASR Lattice Pruning for Translation. ... or word lattices [24, 25]. N-Best translation is straightforward: a text-based SMT. -
Automatic Speech Recognition and Statistical Machine Translation…
mi.eng.cam.ac.uk/~wjb31/ppubs/LMathiasDefenseDec07.pdf16 Feb 2008: 32. 34. 36. 38. 40. 42. 44. 8 10 12 14 16 18 20 22 24. ... Lambert Mathias 24 / 43. MotivationProblem Definition. Discriminative Objective functionGrowth Transformations for MT. -
K. Yu, M.J.F. Gales and P.C. Woodland Cambridge University ...
mi.eng.cam.ac.uk/~mjfg/yu-interspeech07.pdf11 Jan 2008: ML MPE ML MPE. S0 15.1 13.6 29.3 25.40.00 13.8 12.0 27.7 24.80.80 13.5 11.7 26.9 ... Conf. bnmdev06 bcmdev05Thresh. ML MPE ML MPE. 0.00 13.8 12.0 27.7 24.80.76 13.6 11.8 27.5 24.30.80 13.5 11.7
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