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PHONETIC AND GRAPHEMIC SYSTEMS FOR MULTI-GENRE BROADCASTTRANSCRIPTION …
mi.eng.cam.ac.uk/~ar527/wang_icassp2018.pdf4 Nov 2018: When more powerful. This research was partly funded under the ALTA Institute, Universityof Cambridge. ... ForEnglish, it is straightforward to form this from the 26 alphabet letters/a-z/. -
Use of Graphemic Lexicons for Spoken Language Assessment K.M. ...
mi.eng.cam.ac.uk/~ar527/knill_is2017.pdf15 Jun 2018: Thanks to Cambridge English Language Assessment forsupporting this research and providing access to the BULATS data. ... Cambridge Uni-versity Press, 2001. [21] F. Diehl, M. J. F. Gales, X. -
Impact of ASR Performance on Free Speaking Language Assessment ...
mi.eng.cam.ac.uk/~ar527/knill_is2018.pdf15 Jun 2018: The alphabet letters /a-z/ formthe base grapheme set, with two additional root graphemes,/G00,G01/, to model hesitation events. ... 32] S. Young et al., The HTK book (for HTK version 3.5).University of Cambridge, 2015. -
PHONETIC AND GRAPHEMIC SYSTEMS FOR MULTI-GENRE BROADCASTTRANSCRIPTION …
mi.eng.cam.ac.uk/~mjfg/ALTA/publications/ICASSP2018_YuWang.pdf12 Sep 2018: When more powerful. This research was partly funded under the ALTA Institute, Universityof Cambridge. ... ForEnglish, it is straightforward to form this from the 26 alphabet letters/a-z/. -
Semantic object classes in video: A high-definition ground truth…
mi.eng.cam.ac.uk/~cipolla/publications/article/2009-PR-car-video-database.pdf13 Mar 2018: The MicrosoftResearch Cambridge database (Shotton et al., 2006) is among themost relevant, because it includes per-pixel class labels for everyphotograph in the set. ... Processing the CamVid Database using TextonBoost gave verysimilar overall scores to -
Semantic object classes in video: A high-definition ground truth…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2009-PR-car-video-database.pdf13 Mar 2018: The MicrosoftResearch Cambridge database (Shotton et al., 2006) is among themost relevant, because it includes per-pixel class labels for everyphotograph in the set. ... Processing the CamVid Database using TextonBoost gave verysimilar overall scores to -
doi:10.1016/j.patrec.2008.04.005
mi.eng.cam.ac.uk/~cipolla/publications/article/2009-PR-car-video-database-report.pdf13 Mar 2018: The MicrosoftResearch Cambridge database (Shotton et al., 2006) is among themost relevant, because it includes per-pixel class labels for everyphotograph in the set. ... Processing the CamVid Database using TextonBoost gave verysimilar overall scores to -
doi:10.1016/j.patrec.2008.04.005
mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2009-PR-car-video-database-report.pdf13 Mar 2018: The MicrosoftResearch Cambridge database (Shotton et al., 2006) is among themost relevant, because it includes per-pixel class labels for everyphotograph in the set. ... Processing the CamVid Database using TextonBoost gave verysimilar overall scores to -
IB-interestpoints.dvi
mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2018-IB-handout2.pdf14 May 2018: University of Cambridge. Engineering Part IB. Paper 8 Information Engineering. Handout 2: Feature Extraction. ... animals, wood and skin. They typically consist of organised. patterns of regular sub-elements called textons. -
Efficiently Combining Contour and TextureCues for Object Recognition…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2008-BMVC-Shotton.pdf13 Mar 2018: Efficiently Combining Contour and TextureCues for Object Recognition. Jamie Shotton† Andrew Blake† Roberto Cipolla†Microsoft Research Cambridge University of Cambridge. ... animals). We improve on [23] by using more powerful densetexture-based
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