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4 BEAR, TAYLOR: VISUAL SPEECH RECOGNITION: A MINI REVIEW ...
mi.eng.cam.ac.uk/UKSpeech2017/posters/h_bear_poster2.pdf23 Dec 2017: To builda speaker dependent lipreading system, we can use, for example, 800 utterances as trainingsamples and 200 as test samples. ... and we wouldtest on the 200 samples of speaker Y and vice versa. -
Template.dvi
mi.eng.cam.ac.uk/~mjfg/CUED-Chen-RNNLMKWS.pdf22 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. -
University of CambridgeEngineering Part IB Information Engineering…
mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2017-DNN-lecture-3.pdf18 May 2017: Detection The algorithm has to specify for each image mul-. tiple classes (from a choice of 200) and their locations in. -
maneval_hvd_new.eps
mi.eng.cam.ac.uk/~mjfg/thesis_xc257.pdf9 May 2017: Scalable Recurrent Neural Network. Language Models for Speech. Recognition. Xie Chen. Department of Engineering. University of Cambridge. This dissertation is submitted for the degree of. Doctor of Philosophy. Clare Hall College March 2017. I would -
Published as a conference paper at ICLR 2016 TRAINING ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2016-ICLR-low-rank-filter.pdf14 Jan 2017: Mul. tiply. -Acc. Ope. ratio. ns. 0. 200. 400. 600. CPU. -
Published as a conference paper at ICLR 2016 TRAINING ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2016-ICLR-low-rank-filter.pdf14 Jan 2017: Mul. tiply. -Acc. Ope. ratio. ns. 0. 200. 400. 600. CPU. -
Joint Training Methods for Tandem and Hybrid Speech Recognition…
mi.eng.cam.ac.uk/~cz277/doc/Thesis-PhD.pdf11 Jul 2017: Joint Training Methods for Tandem andHybrid Speech Recognition Systems. using Deep Neural Networks. Chao Zhang. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofDoctor of Philosophy. Peterhouse July
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