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1 - 10 of 16 search results for KaKaoTalk:ZA31 24 24 |u:mi.eng.cam.ac.uk where 0 match all words and 16 match some words.

  1. Results that match 2 of 3 words

  2. Deep Learning for Speech Recognition

    mi.eng.cam.ac.uk/~mjfg/LxMLS17.pdf
    29 Nov 2017: Network Interpretation [24]. Standard /ay/ Stimulated /ay/. • Deep learning usually highly distributed - hard to interpret• awkward to adapt/understand/regularise• modify training - add stimulation regularisation• improves ASR performance.

  3. Template.dvi

    mi.eng.cam.ac.uk/~ar527/chen_icassp2017a.pdf
    22 Mar 2017: Mongolian FLP 511K 24.0K - 4.19 12.19WEB 139M 199.8K 0.93 2.10 5.62. ... 24,no. 11, pp. 2146–2157, 2016. [15] Xie Chen, Yongqiang Wang, Xunying Liu, Mark Gales, andP.

  4. STIMULATED TRAINING FOR AUTOMATIC SPEECH RECOGNITION ANDKEYWORD…

    mi.eng.cam.ac.uk/~ar527/ragni_icassp2017b.pdf
    22 Mar 2017: These weretrained on FLP data of 24 Babel languages and CTS data of 4 addi-tional languages, English, Spanish, Arabic and Mandarin, releasedby LDC. ... Stacked Hybrids were trained withand without stimulated training using monophone initialisation

  5. Template.dvi

    mi.eng.cam.ac.uk/~mjfg/CUED-Chen-RNNLMKWS.pdf
    22 Mar 2017: Mongolian FLP 511K 24.0K - 4.19 12.19WEB 139M 199.8K 0.93 2.10 5.62. ... 24,no. 11, pp. 2146–2157, 2016. [15] Xie Chen, Yongqiang Wang, Xunying Liu, Mark Gales, andP.

  6. MORPH-TO-WORD TRANSDUCTION FOR ACCURATE AND EFFICIENT AUTOMATICSPEECH …

    mi.eng.cam.ac.uk/~ar527/ragni_icassp2017a.pdf
    22 Mar 2017: FLP Web FLP Web (#) ASR KWSSwahili 294 – 24.4 0 8.2 8.5 19.6Dholuo 467 1,217 17.5 18.8 6.1 3.0 10.0Amharic 388 ... 4, pp. 1738–1752, 1990. [24] P. Ghahremani, B. BabaAli, D. Povey, K.

  7. STIMULATED TRAINING FOR AUTOMATIC SPEECH RECOGNITION ANDKEYWORD…

    mi.eng.cam.ac.uk/~mjfg/CUED-Ragni-Stimulated-ASR-KWS.pdf
    22 Mar 2017: These weretrained on FLP data of 24 Babel languages and CTS data of 4 addi-tional languages, English, Spanish, Arabic and Mandarin, releasedby LDC. ... Stacked Hybrids were trained withand without stimulated training using monophone initialisation

  8. MORPH-TO-WORD TRANSDUCTION FOR ACCURATE AND EFFICIENT AUTOMATICSPEECH …

    mi.eng.cam.ac.uk/~mjfg/CUED-Ragni-Morph-To-Word.pdf
    22 Mar 2017: FLP Web FLP Web (#) ASR KWSSwahili 294 – 24.4 0 8.2 8.5 19.6Dholuo 467 1,217 17.5 18.8 6.1 3.0 10.0Amharic 388 ... 4, pp. 1738–1752, 1990. [24] P. Ghahremani, B. BabaAli, D. Povey, K.

  9. Low-Resource Speech Recognition and Keyword-Spotting

    mi.eng.cam.ac.uk/~mjfg/SPECOM_2017.pdf
    29 Nov 2017: 23/63. Stimulated Systems. /ey//em/. /sil/. /sh/. /ow/ /ay/. 24/63. Stimulated Network Training. •

  10. University of CambridgeEngineering Part IB Information Engineering…

    mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2017-DNN-lecture-3.pdf
    18 May 2017: the 9 filters create 9 images, which have 9 24 24 = 5184pixels, and thus we need 51,840 parameters to reduce those.

  11. 1 Statistical Sequence ModellingMark Gales Speech recognition and…

    mi.eng.cam.ac.uk/~mjfg/sequence17-draft.pdf
    24 May 2017: Tt=1. p(yt|ht,h̃t) (1.24). where the normalisation term ensures that this is valid PDF. ... 24. Fcml(λ;D) =n. i=1. log( p(w(i)1:L(i)|Y(i). 1:T (i) ; λ)) (1.100).

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