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15 Jun 2005: This is best illustrated by exam-ining maximum margin training of a univariate Gaussian class-conditional distribution.

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''.

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

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. •

19 Jan 2012: This paper exam-ines one form of these models, structured support vector ma-chines (SVMs), for noise robust speech recognition.

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

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.

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 =

20 Feb 2018: lstm). Exam-ple dialogue acts and their top-5 realisations areshown in Table 5.

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.