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1 - 10 of 17 search results for KaKaoTalk:vb20 200 |u:mi.eng.cam.ac.uk where 0 match all words and 17 match some words.

  1. Results that match 1 of 2 words

  2. UKspeech2017

    mi.eng.cam.ac.uk/UKSpeech2017/posters/y_wang.pdf
    17 Nov 2017: Eval{1,2,3} sets (about 13 hours) contain spontaneous speech from 200 speakers with Gujarati, LA Spanish and mixed L1s, respectively. ... 5. Parse Tree. 7. Conclusion. Trn3 set contains trn1 and 200 hours selected from the unsupervised set.

  3. IB-interestpoints.dvi

    mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2017-IB-handout2.pdf
    18 May 2017: mark edges. 0 200 400 600 800 1000 1200 1400 1600 1800 2000. ... Ker. nel. 0 200 400 600 800 1000 1200 1400 1600 1800 2000.

  4. 1 000 001 002 003 004 005 006 007 ...

    mi.eng.cam.ac.uk/~ar527/malinin_acl2017.pdf
    19 Apr 2017: Thisarchitecture is a Deep Density Network (DDN),. 3. 200. 201. 202.

  5. Low-Resource Speech Recognition and Keyword-Spotting

    mi.eng.cam.ac.uk/~mjfg/SPECOM_2017.pdf
    29 Nov 2017: 44/63. Unique-Arcs-Per-Second Pruning - Impact. 0. 50. 100. 150. 200. 250.

  6. TEMPLATE DESIGN © 2008www.PosterPresentations.com Phase Processing…

    mi.eng.cam.ac.uk/UKSpeech2017/posters/e_loweimi.pdf
    17 Nov 2017: c) (d). 0 50 100 150Frame Index. 0. 100. 200. 300. ... 100. 200. 300. 400. Frequency. (H. z). k 0 = 3 k 0 = 5 k 0 = 7.

  7. University of CambridgeEngineering Part IB Information Engineering…

    mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2017-DNN-lecture-2.pdf
    18 May 2017: 4. 6. 0 50 100 150 200 250 300Instances. 0.3. 0.4. ... 4. 2. 0. 2. 4. 6. 0 50 100 150 200 250 300Instances.

  8. Language Independent Bootstrapping for Automatic Speech Recognition…

    mi.eng.cam.ac.uk/UKSpeech2017/posters/a_ragni.pdf
    17 Nov 2017: 403. 404. 50. 100. 150. 200. 250. 300. 350. 3762 7. ... I Cumulative state data usage statistics for 3-hour configuration (VLLP). 100 200 300 400 5000.

  9. Template.dvi

    mi.eng.cam.ac.uk/~ar527/chen_icassp2017a.pdf
    22 Mar 2017: 5.1. Acoustic Models. The full language pack (FLP) in the Babel Program contains about100-200 hours of transcribed audio training data (60-80 hoursspeech) for acoustic model training.

  10. summaOverviewPoster.key

    mi.eng.cam.ac.uk/UKSpeech2017/posters/s_renals.pdf
    17 Nov 2017: BBC Monitoring 200 journalists monitoring global audio, video, text news. Deutsche Welle Multilingual content generation and management.

  11. Comparison between Hessian Free and Natural Gradient training for DNN …

    mi.eng.cam.ac.uk/UKSpeech2017/posters/a_haider.pdf
    20 Nov 2017: Linear Conjugate Gradient. Experimental Setup. I Experiments used ASRU 2015 MGB challenge data.I Training set : 200 hr MGB1 training dataset.I Validation : the official MGB1 dev.sub set (5.5

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