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11 - 20 of 468 search results for katalk:PC53 24 / |u:mi.eng.cam.ac.uk where 0 match all words and 468 match some words.

  1. Results that match 1 of 2 words

  2. The Knowledge Engineering Review, Vol. 00:0, 1–24. c© 2006, ...

    mi.eng.cam.ac.uk/~sjy/papers/swsy06.pdf
    20 Feb 2018: The Knowledge Engineering Review, Vol. 00:0, 1–24. c 2006, Cambridge University PressDOI: 10.1017/S000000000000000 Printed in the United Kingdom.

  3. Use of Graphemic Lexicons for Spoken Language Assessment K.M. ...

    mi.eng.cam.ac.uk/~ar527/knill_is2017.pdf
    15 Jun 2018: In [24] phonetic pronunciation features consisting ofa set of phone-pair distances were proposed for vowels and ap-plied to read speech. ... 8, no. 4, pp. 369–394, 1994. [24] N. Minematsu, S. Asakawa, and K.

  4. Emotion Conversion using F0 Segment Selection Zeynep Inanoglu, Steve…

    mi.eng.cam.ac.uk/~sjy/papers/inyo08.pdf
    20 Feb 2018: wwpos 24.52 11.29 18.47wspos 11.33 4.91 3.31wpof s 1.13 4.82 8.82wppof s 24.27 6.49 10.54wonset 15.08 0.33 ... 47.3% 52.7%. 75.3% 24.7%. Figure 3: Categorical quality ratings for spectral conversion duration conversion HMM-based contour generation.

  5. ./plot_entropy.eps

    mi.eng.cam.ac.uk/~ar527/chen_is2017.pdf
    15 Jun 2018: 24,no. 8, pp. 1438–1449, 2016.

  6. ON-LINE POLICY OPTIMISATION OF BAYESIAN SPOKEN DIALOGUE SYSTEMS…

    mi.eng.cam.ac.uk/~sjy/papers/gbhk13.pdf
    20 Feb 2018: 3.3. The agenda-based simulated user. The agenda-based user simulator [24, 25] factorises the user stateinto an agenda and a goal. ... 23] TopTable, “TopTable,” 2012, https://www.toptable.com. [24] J Schatzmann, Statistical User and Error Modelling

  7. Impact of ASR Performance on Free Speaking Language Assessment ...

    mi.eng.cam.ac.uk/~ar527/knill_is2018.pdf
    15 Jun 2018: Word levelconfidence scores are returned from the Kaldi [24] decoderwhich are frame weighted and undergo a piece-wise mappingfor use in error detection. ... 3660–3664. [24] D. Povey et al., “The Kaldi Speech Recognition Toolkit,” in Proc.of the

  8. BAYESIAN DIALOGUE SYSTEM FOR THE LET’S GO SPOKEN DIALOGUE ...

    mi.eng.cam.ac.uk/~sjy/papers/tykg10.pdf
    20 Feb 2018: In control tests by humanusers, the success rate of the system was 24.5% higher thanthe baseline Lets Go! ... Com-pared to the BASELINE system, the BUDSLETSGO systemimproves the dialogue success rate by 24.5% and the worderror rate by 9.7%.

  9. DISTRIBUTED DIALOGUE POLICIES FOR MULTI-DOMAIN STATISTICAL…

    mi.eng.cam.ac.uk/~sjy/papers/gkty15.pdf
    20 Feb 2018: 24, no. 4, pp. 562–588, 2010. [13] M Gašić, C Breslin, M Henderson, D Kim, M Szummer,B Thomson, P Tsiakoulis, and S Young, “POMDP-based dia-logue manager adaptation

  10. Dialogue manager domain adaptation using Gaussian process…

    mi.eng.cam.ac.uk/~sjy/papers/gmrs17.pdf
    20 Feb 2018: SFRName Reward Success #Turnsbest prior 8.66 0.35 85.40 2.19 8.32 0.20adapted 9.62 0.30 89.60 1.90 8.24 0.19. ... The systemwas deployed in a telephone-based set-up, with subjects recruited via Ama-zon MTurk and a recurrent neural network model was used

  11. PROBABLISTIC MODELLING OF F0 IN UNVOICED REGIONS IN HMM ...

    mi.eng.cam.ac.uk/~sjy/papers/ytgk09.pdf
    20 Feb 2018: The static feature set comprised 24 Mel-Cepstral coefficients,logarithm of F0 and aperiodic energy components in five frequency. ... 12 sentences werethen randomly selected to make up a testset for each listener, leadingto 24 wave files pairs (12 for

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