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31 - 40 of 1,000 search results for katalk:za33 24 |u:mi.eng.cam.ac.uk where 0 match all words and 1,000 match some words.

  1. Results that match 1 of 2 words

  2. EFFICIENT LATTICE RESCORING USINGRECURRENT NEURAL NETWORK LANGUAGE…

    mi.eng.cam.ac.uk/~mjfg/xl207_ICASSP14a.pdf
    28 Apr 2014: Instead, previous research has beenfocused on using N-best list rescoring for RNNLM performanceevaluation [13, 14, 26, 27, 24]. ... 21, no. 3, pp. 492–518,2007. [24] Y. Si, Q. Zhang, T.

  3. Addressing Objects and Their Relations:The Conversational Entity…

    mi.eng.cam.ac.uk/~sjy/papers/ubcr18.pdf
    3 Jul 2018: shows that the CEDM learns to address a relationin up to 24.5% of all dialogues for r = 1.0. ... Computer Speech & Lan-guage, 24(2):150–174. Steve J. Young, Milica Gašić, Blaise Thomson, and Ja-son D.

  4. On-line Active Reward Learning for Policy Optimisationin Spoken…

    mi.eng.cam.ac.uk/~sjy/papers/sgmb16.pdf
    20 Feb 2018: Thomson and Young2010] Blaise Thomson and SteveYoung. 2010. Bayesian update of dialogue state:A pomdp framework for spoken dialogue systems.Computer Speech and Language, 24:562–588.

  5. Optimisation for POMDP-based Spoken Dialogue Systems M. Gašić, F.…

    mi.eng.cam.ac.uk/~sjy/papers/gjty12.pdf
    20 Feb 2018: To obtain a closed formsolution of (24), the policy π must be differentiable with respect to θ. ... 10. To lower the variance of the estimate of the gradient, a constant baseline, B, can beintroduced into (24) without introducing any bias [22].

  6. IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, JANUARY…

    mi.eng.cam.ac.uk/~sjy/papers/gayo14.pdf
    20 Feb 2018: An advantage of this sparsification approach is that itenables non-positive definite kernel functions to be used in theapproximation, for example see [24]. ... It has already beenshown that active learning has the potential to lead to fasterlearning [24]

  7. crosseval_diff-reward2b.ps

    mi.eng.cam.ac.uk/~sjy/papers/kgjm10.pdf
    20 Feb 2018: Yu. 2009. The Hidden InformationState model: a practical framework for POMDPbased spoken dialogue management.ComputerSpeech and Language, 24(2):150–174.

  8. Phrase-based Statistical Language Generation usingGraphical Models…

    mi.eng.cam.ac.uk/~sjy/papers/mgjk10.pdf
    20 Feb 2018: Com-puter Speech & Language, 24(4):562–588, 2010. Y. Tokuda, T. Yoshimura, T. ... Computer Speech and Language,24(2):150–174, 2010.

  9. DISCRIMINATIVE SPOKEN LANGUAGE UNDERSTANDINGUSING WORD CONFUSION…

    mi.eng.cam.ac.uk/~sjy/papers/hgtt12.pdf
    20 Feb 2018: 24, no. 4, Oct. 2010. [16] S. J. Young, G. Evermann, M.

  10. From Discontinuous To Continuous F0 Modelling In HMM-based…

    mi.eng.cam.ac.uk/~sjy/papers/yuty10.pdf
    20 Feb 2018: The feature set includes 24 spectralcoefficients, log F0 and 5 aperiodic component features.

  11. Practicable Assessment of Cochlear Sizeand Shape from Clinical CT ...

    mi.eng.cam.ac.uk/reports/svr-ftp/gee_tr004.pdf
    27 Jul 2020: CBCT non-planarity 2.47 2.46 3.35 15.7 16.0 14.8 12.1 10.8 8.63reach 9.36 9.16 9.57 26.7 24.7 ... MDCT non-planarity 3.04 3.67 4.52 15.1 14.2 15.5 11.7 10.6 8.3reach 13.6 11.2 10.4 26.3 24.1

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