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Did you mean economicsadam |u:mi.eng.cam.ac.uk?
51 - 60 of 184 search results for Economics exam |u:mi.eng.cam.ac.uk where 2 match all words and 182 match some words.

  1. Results that match 1 of 2 words

  2. lect3_pres.dvi

    mi.eng.cam.ac.uk/~mjfg/local/4F10/lect3_pres.pdf
    10 Nov 2015: Therefore the overall procedure is. 1. Initialise the parameters of the mixture, θ(0), - for exam-ple set all component priors to be equal, all variances tobe equal, and use different

  3. UNICODE-BASED GRAPHEMIC SYSTEMS FOR LIMITED RESOURCE LANGUAGES M.J.F. …

    mi.eng.cam.ac.uk/~ar527/gales_icassp2015a.pdf
    21 Jan 2015: obtained from using the FLP LM. What is more interesting is thatgraphemes not seen in the acoustic model training data, for exam-ple “һ”, exist in the recognition output (and correctly).

  4. Towards Learning Orientated Assessment for Non-native Learner Spoken…

    mi.eng.cam.ac.uk/~kmk/presentations/ALTA_Sheffield_20190306.pdf
    8 Mar 2019: σ. g2. f. Grader Performance. 26. Grader PCC MSE. Exam 8.48 0.864.

  5. lect13.dvi

    mi.eng.cam.ac.uk/~mjfg/local/4F10/lect13_pres.pdf
    25 Nov 2015: These approaches are called non-parametric. We havealready seen a classifier that is based on the training exam-ples, support vector machines (Gaussian processes are an-other example).

  6. Multilingual Models in Neural Machine Translation

    mi.eng.cam.ac.uk/~wjb31/MPhil_Thesis_Guangyu_Yang.pdf
    21 Nov 2023: Multilingual Models in Neural MachineTranslation. Guangyu Yang. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Clare Hall August

  7. Morph-fitting: Fine-Tuning Word Vector Spaceswith Simple…

    mi.eng.cam.ac.uk/~sjy/papers/vmro17.pdf
    20 Feb 2018: pushing antonymous exam-ples away from each other. ... formed vector space, see Fig. 1). Tab. 1 illustratesthe effects of morph-fitting by qualitative exam-ples in three languages: the vast majority of nearestneighbours are “morphological” synonyms.

  8. WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN ...

    mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp06.pdf
    9 Dec 2006: For exam-ple, speaker models can be built for people who are likely to be inthe broadcast (such as prominent politicians or main news anchorsand reporters). ... However, this method relies on previously seen exam-ples of the test speakers, which is not

  9. Neural Belief Tracker: Data-Driven Dialogue State Tracking Nikola…

    mi.eng.cam.ac.uk/~sjy/papers/mowt17.pdf
    20 Feb 2018: FOOD=CHEAP: [affordable, budget, low-cost,low-priced, inexpensive, cheaper, economic,. ]. RATING=HIGH: [best, high-rated, highly rated,top-rated, cool, chic, popular, trendy,. ].

  10. DEVELOPMENT OF A PHONETIC SYSTEM FOR LARGE VOCABULARY ARABICSPEECH ...

    mi.eng.cam.ac.uk/~mjfg/gales-asru07.pdf
    11 Jan 2008: alif, for exam-ple, from a word that Buckwalter could derive a pronunciation wereincluded with the mapped pronunciation (map).

  11. Log-Linear System Combination Using Structured Support Vector Machines

    mi.eng.cam.ac.uk/~mjfg/interspeech16_combSSVM.pdf
    26 Sep 2016: To address this problem, this paper exam-ines schemes based on log-linear score combination. ... 13] exam-ines combination of hybrid and tandem systems with log-linearmodels, and applies learnt phone-specific combination weightsto frame level joint

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