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  2. UK Speech Conference 2017

    mi.eng.cam.ac.uk/UKSpeech2017/
    17 Nov 2017: friends and make new ones.
  3. How Does the Femoral Cortex Depend onBone Shape? A ...

    mi.eng.cam.ac.uk/reports/svr-ftp/gee_tr704.pdf
    15 Jun 2017: As the armature bends, the mesh vertices aredragged to their new positions by their respective bones. ... 14. density at broad regions of interest, the apparent increase in CMSD with increasing neck-shaft angle at thecalcar femorale is a new finding and
  4. summaOverviewPoster.key

    mi.eng.cam.ac.uk/UKSpeech2017/posters/s_renals.pdf
    17 Nov 2017: Sentiment Extraction. SUMMA PlatformDatabase. VisualisationsPrototypes. SUMMA PlatformSUMMA Aimsmonitor hundreds of live news sources transcribe spoken content in different languages translate content into English organise news streams into
  5. Deep Activation Mixture Model for Speech Recognition

    mi.eng.cam.ac.uk/UKSpeech2017/posters/c_wu.pdf
    17 Nov 2017: l)k. ). 6. Experiment. I Data and setupI 144-hour English broadcast news dataset (LDC97S44, LDC98S71)I DNN-HMM hybrid ASR frameworkI 5 hidden layers with 1024 units for both DNN
  6. .poster_jeremy_v2.tex.dvi

    mi.eng.cam.ac.uk/UKSpeech2017/posters/j_wong.pdf
    17 Nov 2017: HUB4: English broadcast news. 144 hours training set, 6000 PDT states. •
  7. Modular Construction of Complex Deep Learning Architectures in HTK

    mi.eng.cam.ac.uk/UKSpeech2017/posters/f_kreyssig.pdf
    20 Nov 2017: I New Layer-Types such as CNN, GRU and LSTM layers areintroduced to HTK.
  8. Genigraphics Research Poster Template A0/A1

    mi.eng.cam.ac.uk/UKSpeech2017/posters/m_al-radhi.pdf
    17 Nov 2017: show the effect of adding Harmonics-to-Noise Ratio (HNR) as a new excitation parameter to the Continuous vocoder (see Fig.
  9. 4 BEAR, TAYLOR: VISUAL SPEECH RECOGNITION: A MINI REVIEW ...

    mi.eng.cam.ac.uk/UKSpeech2017/posters/h_bear_poster2.pdf
    23 Dec 2017: This is speaker independent lipreading,see Figure 5. It ensures that the model is learning a classifier that is not biased by the identityof the speaker, and is generalisable to new ... speakers from the training set and new speakers, but speakers must

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