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1 - 10 of 29 search results for katalk:za31 24 / / / / / |u:mi.eng.cam.ac.uk where 0 match all words and 29 match some words.

  1. Results that match 1 of 2 words

  2. K. Yu, M.J.F. Gales and P.C. Woodland Cambridge University ...

    mi.eng.cam.ac.uk/~mjfg/yu-interspeech07.pdf
    11 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

  3. DISCRIMINATIVE LANGUAGE MODEL ADAPTATION FORMANDARIN BROADCAST SPEECH …

    mi.eng.cam.ac.uk/~mjfg/liu-asru07.pdf
    11 Jan 2008: CNN 7.24 12.73 20.48 224.2. Table 5. Model size and text source for English component LMs. ... Adapt Int InitTER%. bnmd06 bcmd05 eval06fixed lin - 72.24 75.28 80.46.

  4. This is a placeholder. Final title will be filled later.

    mi.eng.cam.ac.uk/~mjfg/yu-asru05.pdf
    11 Jan 2008: γm(t)ot. )(24). γm(t) is the component posterior derived from P (θ|O, H, λ̂k1).For the frame independent assumption it is necessary to obtain. ... where G and k are the standard sufficient statistics given in equa-tions 23 and 24, except that γm(t)

  5. Augmented Statistical Models for Classifying Sequence Data Martin…

    mi.eng.cam.ac.uk/~mjfg/thesis_ml362.pdf
    16 Jan 2008: 2.2.2 Hidden conditional random fields (HCRFs). 24. 2.2.3 Parameter estimation for conditional models.

  6. A QUALITY-GUIDED DISPLACEMENTTRACKING ALGORITHM FOR ULTRASONIC…

    mi.eng.cam.ac.uk/reports/svr-ftp/chen_tr593.pdf
    17 Jan 2008: Among several techniques for displacement estimation [12, 24], correlation maximization wasthe first to be proposed and remains the most widely used [16]. ... As p1 is the only point ready for processing,it is selected and fed into any suitable

  7. Bitext Alignment for Statistical Machine Translation

    mi.eng.cam.ac.uk/~wjb31/ppubs/YDengDefenseDec05.pdf
    16 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.

  8. - + Code Breaking for Automatic Speech ...

    mi.eng.cam.ac.uk/~wjb31/ppubs/VenkataramaniThesisTalk05.pdf
    16 Feb 2008: Code Breaking for Automatic Speech Recognition 24 |35). < > -. Studying Segment Set Pruning. Towards studying the ability of lattice pinching in.

  9. Minimum Bayes-Risk Techniques forAutomatic Speech Recognition and…

    mi.eng.cam.ac.uk/~wjb31/ppubs/SKumarPhDefense2004.pdf
    16 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.

  10. Automatic Speech Recognition and Statistical Machine Translation…

    mi.eng.cam.ac.uk/~wjb31/ppubs/LMathiasDefenseDec07.pdf
    16 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.

  11. Bitext Alignment forStatistical Machine Translation Yonggang Deng A…

    mi.eng.cam.ac.uk/~wjb31/ppubs/YDengDissertationDec05.pdf
    16 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

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