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1 - 10 of 29 search results for katalk:PC53 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. NONPARAMETRIC SURFACE REGRESSIONFOR STRAIN ESTIMATION J. E. Lindop,…

    mi.eng.cam.ac.uk/reports/svr-ftp/lindop_tr598.pdf
    6 Mar 2008: The. 6. 20 40 60 80 100sample number. ry=24 a. ry=44 a. ... a). 20 40 60 80 100sample number. ry=24 a. ry=44 a.

  3. 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

  4. DISCRIMINATIVE LANGUAGE MODEL ADAPTATION FORMANDARIN BROADCAST SPEECH …

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/liu-asru07.pdf
    26 Mar 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.

  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. - + 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.

  7. ��������� �� � ������������������� ��� ��� �!…

    mi.eng.cam.ac.uk/~wjb31/ppubs/VlasiosDoumpiotisDissOct04.pdf
    16 Feb 2008: "$#&%'(),.-%/01 " 2-3 2 42 56879;:<=1) >?1 01@ " ABC". DE F(GH42IJKC7 #%L88NM :O88 F1@ ". PQSRUTWVYXUT&ZX[1]_VYXCaVYT.

  8. is2008.dvi

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/raut-interspeech08.pdf
    3 Dec 2008: SI — MLLR 24.3 27.0MLLR MLLR 23.6 26.4. DSAT DLT DLT 18.4 28.1MLLRDMT MLLRDMT 22.5 25.3.

  9. tech.dvi

    mi.eng.cam.ac.uk/reports/svr-ftp/hsu_tr584.pdf
    5 Sep 2008: µPRA = pW TWS TSI TspI′. (24). This is a measurement of system accuracy, and includes errors from every component of thesystem.

  10. Covariance Modelling for Noise-Robust Speech Recognition R. C. van ...

    mi.eng.cam.ac.uk/~mjfg/vandalen_INTER08.pdf
    16 Jun 2008: 20 I. 2. –24. yst1yst. yst1. 35 = Dyet (13). where D is the dynamic coefficient matrix and yet is the vectorof static coefficients in the appropriate window.

  11. Model-Based Approaches to Robust SpeechRecognition Mark Gales with…

    mi.eng.cam.ac.uk/~mjfg/talk_kcl.pdf
    13 Jun 2008: Cambridge UniversityEngineering Department. King’s College London Seminar 24. Model-Based Approaches to Robust Speech Recognition. ... p(Y; λ(1)). )λ(2) log. (p(Y; λ(2)). ). . – Related to the Fisher kernel [24].

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