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MultiMedia Document Retrieval (1997-2000)
mi.eng.cam.ac.uk/research/projects/Multimedia_Document_Retrieval/7 Oct 2001: May 1998 - The TREC-7 Evaluation. The overall word error rate for our recognition system on the 100 hours of TREC-7 SDR data was 24.8%, the lowest in the -
LARGE SCALE DISCRIMINATIVE TRAINING FORSPEECH RECOGNITION P.C.…
mi.eng.cam.ac.uk/reports/svr-ftp/woodland_asr00.pdf6 Nov 2000: Some discriminative training schemes, such as frame-discrimination [14, 24], try to over-generate training set con-fusions to improve generalisation. ... In [24] it was shownthat the improvements obtained by FD were at least as goodas those reported by -
Uncertainty: Knowing What You Don't Know
mi.eng.cam.ac.uk/~mjfg/mjfg_cncc2021.pdf20 Jun 2023: 24/36. Spoken Language Assessment. 25/36. Grader Uncertainty: Ensemble-Based. Within 0.5 CEFR-Level Within 1.0 CEFR-Level26/36. -
MultiMedia Document Retrieval (1997-2000) - Progress
mi.eng.cam.ac.uk/research/projects/Multimedia_Document_Retrieval/progress.html7 Oct 2001: The overall word error rate for the data was 24.8%, the lowest in the TREC-7 SDR evaluation, with the baselines provided by NIST offering 33 and 42%. ... The final project publications include the TREC-9 paper [24] , two papers in the International -
Unsupervised Bayesian Detection of Independent Motion in Crowds…
mi.eng.cam.ac.uk/reports/svr-ftp/brostow_MotionInCrowdsCVPR06.pdf14 Sep 2006: 24, 18]. Both systems group an image’sspatial features, performing a global annealing optimizationthat propagates the certainty at distinct person-boundaries touncertain areas where those people’s outlines are ambigu-ous. ... 24] P. Tu and J. -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/logan_sst96.pdf9 Aug 2005: #"$%&')(,-.%%&( 0/-#1""324%5/246"78&9:5. ;<8<'7>=@?9A@BA@BDCE<8F@<'8=HGIBDJK=B&L>MNMNO>PQ'/I JRI =BSA@BDCT8=G>=UVI ONJW(XY=ZL@Q. "M>L[AXYU]M>BDU=>_8B?IBDMNM>XaIBD?HQ.BI bDM>XcJ4I Ued=>_#'A@]G[XaI C?@M. ;'&'f2#PI JL[A@L[M>XCMNJKO>XgI,G[MNJABDMNhA@i? @ -
paper.dvi
mi.eng.cam.ac.uk/~mjfg/ragni_ASRU11.pdf20 Dec 2011: 24, pp. 648–662, 2010. [5] S.-X. Zhang, A. Ragni, and M. -
Joint Uncertainty Decoding for Noise Robust Speech Recognition H. ...
mi.eng.cam.ac.uk/~mjfg/liao_INTER05.pdf19 Dec 2006: Uncertainty 1 4 16 256. Clean — 33.2. SPLICENo. 24.6 20.7 17.0 12.3FE-CMLLR 16.3 15.3 12.8 13.5. -
MORTGAGE DEFAULT: CLASSIFICATION TREES ANALYSIS David Feldman* and…
mi.eng.cam.ac.uk/~mjfg/local/4F10/Feldman_Gross.pdf15 Nov 2005: MORTGAGE DEFAULT: CLASSIFICATION TREES ANALYSIS. David Feldman and Shulamith Gross#. March 24, 2003. ... 24. robust Cross-Validation method. Since it does not have any particular. -
Context adaptive training with factorized decisiontrees for HMM-based …
mi.eng.cam.ac.uk/~sjy/papers/yzmy11.pdf20 Feb 2018: 24].3 Available at http://mi.eng.cam.ac.uk/˜farm2/emphasis.4 Cohen’s Kappa cannot be used here because the phrases are not distinct elements. ... Interspeech, 2010, pp. 410–413. [24] S. Young, G. Evermann, M. Gales, T. -
TWO-WAY CLUSTER VOTING TO IMPROVE SPEAKER DIARISATION PERFORMANCE S.…
mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp05.pdf25 Mar 2005: shows. The DER is 24.16%(28.05%) if the best(worst) input istaken independently for each show. ... true reference speakers, so when scoringagainst the reference, the supergroups may no longer be treated indepen-dently thus dramatically increasing the -
INVESTIGATION OF ACOUSTIC MODELING TECHNIQUES FOR LVCSR SYSTEMS X. ...
mi.eng.cam.ac.uk/reports/svr-ftp/liu_icassp2005.pdf19 May 2005: Systemeval03. dev04s25 fsh Avg. P2-cn HLDA 26.6 18.4 22.6 18.7. P3a-cn SAT 24.5 17.1 20.9 17.3P3c-cn SPron 24.7 ... cn SPAM 24.1 16.9 20.6 17.2P3h-cn SATSPAM 23.9 16.9 20.5 16.8P3i-cn CTRL 24.5 17.5 21.1 17.6. -
WILLIAM JOSEPH BYRNE III Department of Engineering 16 Water ...
mi.eng.cam.ac.uk/~wjb31/byrnecv.pdf9 Nov 2023: Talk. [24] Context-dependent alignment models and hierarchical phrase-based translation with weighted finite state trans-ducers, GALE PI Meeting, Tampa, FL, USA, May 2009. ... Association for Computational Linguistics, November 2021. [24] BO-HSIANG TSENG, -
Still Talking to Machines (Cognitively Speaking) Steve Young…
mi.eng.cam.ac.uk/~sjy/papers/youn10a.pdf20 Feb 2018: partition ex-plicitly records the fact that x = a and the existing partitionis updated to record the fact that x = ā [24]. -
INDICATOR VARIABLE DEPENDENT OUTPUT PROBABILITY MODELLING…
mi.eng.cam.ac.uk/~sjy/papers/tuyo01.pdf20 Feb 2018: error rate of 33.2 %, and for the first and secondorder derivatives the error rates of the classifiers are 33.1 %and 24.2 %, respectively. ... 24.8 42.4par 22.7 13.1 21.7 32.4 32.7 25.2 27.4 45.1. -
Part Name Part Image Part Weight [mg] Electric, Motor ...
mi.eng.cam.ac.uk/IALego/helicopter_files/helicopter_weights.pdf1 Jan 2024: 1300. Light Bluish Gray Technic, Gear 24 Tooth (New Style. with Single Axle Hole). -
The Cambridge Multimedia Document Retrieval (MDR) Project : Summary…
mi.eng.cam.ac.uk/reports/full_html/sparckjones_cltr517.html/10 Oct 2001: X) 64.95 61.25 46.82 45.24 44.27 30.33 39.98 42.14 38.65 35.72 BE DBRF2 (X) 66.57 65.89 45.21 ... BE DBRF (X) 69.41 69.12 52.55 51.73 51.14 36.86 41.99 44.13 42.14 42.05 BE [PR]BRF (A) 66.24 64.53 -
Deep Learning for Speech Recognition
mi.eng.cam.ac.uk/~mjfg/LxMLS17.pdf29 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. -
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mi.eng.cam.ac.uk/reports/svr-ftp/sparckjones_cltr517.pdf7 Oct 2001: 8;,=&"vZ$9V K)i!Zi9V ;)Î$9h ;& ;=!"p;) / -,H;&AP,!#P6 %S+[#( 24 )g(>@{7cPU(.( 7;'8;(! ... 9V @24 Ì ' $;S+[ -c.,=",=&8U - PU -"P7,=!)G,=&,=&,H&8g- / -( -,=,Hg",=-;' - -r( -,!K9$(-v> zXx}24 & -)g=![] Ç4',! -
ICSLPDataCollection-10
mi.eng.cam.ac.uk/~sjy/papers/wiyo04b.pdf20 Feb 2018: Per-turn. WER. Per-dialog WER. None 2 6 24 83 % 0 % 0 % Low 4 12 48 83 % 32 % 28 % Med 4 12 48 77 % 46 % 41 % Hi 2 6 24 ... Dataset. Metrics (task & user sat). R2 Significant predictors. ALL User-S 52 % 1.03 Task ALL User-C 60 % 5.29 Task – 1.54
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