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  2. PII: S0167-6393(99)00044-8

    mi.eng.cam.ac.uk/~sjy/papers/wiyo00.pdf
    20 Feb 2018: For exam-ple, the threshold for a phone p can be dened interms of the mean lp and variance rp of all theGOP scores for phone p in the training data,. ... For exam-ple, Fig. 2 shows the resulting network for theword but''.
  3. 20 Feb 2018: 5 Discriminative Training. In contrast to the traditional ML criteria (Equation 1)whose goal is to maximise the log-likelihood of cor-rect examples, DT aims at separating correct exam-ples
  4. paper.dvi

    mi.eng.cam.ac.uk/~mjfg/sxz20_inter11.pdf
    19 Jan 2012: This paper exam-ines one form of these models, structured support vector ma-chines (SVMs), for noise robust speech recognition.
  5. lect1.dvi

    mi.eng.cam.ac.uk/~mjfg/local/4F10/lect1.pdf
    10 Nov 2015: Web-Page: http://mi.eng.cam.ac.uk/mjfg/4F10/index.html. Assessment by exam (1.5h): 3 questions from 5. A number of books cover parts of the course material. •
  6. 15 Jun 2018: The model is trained on ASR transcriptions of spokenresponses. Due to a lack of off-topic responses, negative exam-ples for both training and evaluation are created by randomlyshuffling prompts and ... is demon-strated on spoken data from the Cambridge
  7. 16 Jun 2008: Only these 16 noise conditions are exam-ined in this work as stereo data is not provided for any of theother noise conditions.
  8. 20 Feb 2018: For exam-ple, if reject(area(centre)) was never ob-served at training time, P(r = centre of town|s =reject(area(centre))) will be estimated bybacking off to P(r =
  9. 22 Nov 2006: For exam-ple, the combination of the S2 and S3 GAUSS systems gave a 0.3%and 0.2% absolute improvements oneval03m and eval04 re-spectively.
  10. 20 Feb 2018: lstm). Exam-ple dialogue acts and their top-5 realisations areshown in Table 5.
  11. 20 Feb 2018: Relaxing questions(”Would you also consider another airline?”), for exam-ple, were anticipated by Levin et al.

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