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21 - 28 of 28 search results for katalk:za33 24 |u:mi.eng.cam.ac.uk where 0 match all words and 28 match some words.

  1. Results that match 1 of 2 words

  2. IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/liu_ASL07.pdf
    10 Oct 2007: This sensitivity to outliers is a well known feature of the MMI criterion [24]. ... j))}. (24). Each Gaussian component is assumed to be independent of all others.

  3. PhD Thesis

    mi.eng.cam.ac.uk/~mjfg/thesis_ky219.pdf
    16 Nov 2007: 2.4.1.2 Minimum Phone Error (MPE) 23. 2.4.1.3 Minimum Classification Error (MCE) 24. ... 2.4.2 Weak-Sense Auxiliary Function and Parameter Re-estimation 24. 2.5 Bayesian Training of HMMs 29.

  4. IEEE TRANS. ON SAP, VOL. ?, NO. ??, ????? ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/kai_ASP07.pdf
    10 Oct 2007: It is also interesting to compare N-Best supervisionto the standard 1-Best supervision adaptation approaches suchas iterative MLLR [24]. ... Zθ(O, H)can be simply calculated using the forward algorithm withp̃(ot|θt),. Zθ(O, H) =. θ. P (θ|M). t.

  5. PhD Thesis

    mi.eng.cam.ac.uk/~mjfg/thesis_kcs23.pdf
    16 Nov 2007: 2.3 Limitations of HMMs for Speech Recognition 24. 2.3.1 Explicit Temporal Correlation Modelling 25.

  6. Discriminative Complexity Control and Linear Projections for Large…

    mi.eng.cam.ac.uk/~mjfg/thesis_xl207.pdf
    16 Nov 2007: 2.5 HLDA and LDA projection 24. 2.6 multiple HLDA projections 25.

  7. Linear Gaussian Models for Speech Recognition Antti-Veikko Ilmari…

    mi.eng.cam.ac.uk/~mjfg/thesis_avir2.pdf
    16 Nov 2007: 3.1 State Space Models 24. 3.2 Bayesian Networks 25. 3.3 State Evolution Process 27. ... bank of triangular filters (eg. 24 channels). This smoothed power spectrum is compressed using.

  8. ATK An Application Toolkit for HTK Version 1.6 Steve ...

    mi.eng.cam.ac.uk/research/dialogue/ATK_Manual.pdf
    20 May 2007: TARGETKIND = MFCC_E_D_N_A. TARGETRATE = 100000.0. USEPOWER = F. NUMCHANS = 24. ... 24. void ATask::FooCmd(). {. int i;. if (GetIntArg(i,0,100)) {. // implement foo(i). }. }.

  9. A Gaussian Mixture Model Spectral Representation for Speech…

    mi.eng.cam.ac.uk/~mjfg/thesis_mns25.pdf
    16 Nov 2007: 2.5.1 Vocal tract length normalisation 24. 2.5.2 Maximum likelihood linear regression 25. ... $ I / (2.23)3 /. $ $ I $ I - $ (2.24) $F 3 3 % / (2.25).

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