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  2. Modular Construction of Complex Deep Learning Architectures in HTK

    mi.eng.cam.ac.uk/UKSpeech2017/posters/f_kreyssig.pdf
    20 Nov 2017: Architecture Width PER7L-RELU-MLP 500 21.439L-SELU-MLP 250 20.8021L-(FC)ResNet 250 20.37CNN 2048 for FC 20.123L-RELU-RNN 1024 18.543L-RELU-BDRNN 750
  3. Part Name Part Image Part Weight [mg] Electric, Motor ...

    mi.eng.cam.ac.uk/IALego/helicopter_files/helicopter_weights.pdf
    1 Jan 2024: 250. Light Bluish Gray Technic, Gear 16 Tooth. 575. Light Bluish Gray Technic, Gear 20 Tooth Double Bevel.
  4. Simplifying very deep convolutional neural network architectures for…

    mi.eng.cam.ac.uk/UKSpeech2017/posters/j_rownicka.pdf
    3 Jul 2018: training set of Aurora4. Model A B C D AVGDNN/clntr 2.71 43.00 24.06 58.66 45.48VDCNN-max-4FC/clntr 2.32 35.99 21.20 ... 53 39.62VDCNN-allconv/clntr 1.98 40.62 20.08 55.57 42.80.
  5. UKspeech2017

    mi.eng.cam.ac.uk/UKSpeech2017/posters/y_wang.pdf
    17 Nov 2017: 0. 20. 40. 60. 80. 100. % o. f Utte. ranc.
  6. MultiMedia Document Retrieval (1997-2000) - Progress

    mi.eng.cam.ac.uk/research/projects/Multimedia_Document_Retrieval/progress.html
    7 Oct 2001: Our word error rate on the 10 hour scored subset of TREC-8 SDR was 20.6% (the lowest in the evaluation). ... The demo was presented at both RIAO 2000 [20] and SIGIR 2000 [22] and attracted considerable interest.
  7. The University of Birmingham 2017 SLaTE CALL Shared Task Systems

    mi.eng.cam.ac.uk/UKSpeech2017/posters/m_qian.pdf
    20 Nov 2017: 50% vs. 20%. • PF-STAR German: German children aged 10-13, 3.38 hours of read speech.Acoustic Model. •
  8. Speaker Diarisation for Broadcast News

    mi.eng.cam.ac.uk/reports/full_html/tranter_odyssey04.html/
    14 Jun 2004: 43.60. CU. PER. 0.4. 0.2. 9.1. 11.60. 29.7. 32.20. MIT. CU. ... MIT. MIT. 2.3. 3.7. 5.6. 25.93. 20.6. 40.96. MIT. PER. 0.6.
  9. Genigraphics Research Poster Template A0/A1

    mi.eng.cam.ac.uk/UKSpeech2017/posters/m_al-radhi.pdf
    17 Nov 2017: 20, no. 1, pp. 102-105, 2013. [4] T. Drugman and Y.
  10. An avatar-based system for identifying individuals likely to develop…

    mi.eng.cam.ac.uk/UKSpeech2017/posters/b_mirheidari.pdf
    17 Nov 2017: Features• Conversation Analysis inspired[3]: 20 features,. e.g. patient answered me for who’s most concernedquestion, average number of empty words (CA is anapproach to study social interaction/ communicationability of
  11. Spoken Document Retrieval for TREC-7 at Cambridge University

    mi.eng.cam.ac.uk/reports/full_html/johnson_trec7.html/
    30 Mar 2000: 20.4. 5.9. 4.8. 31.0. NIST/CMU base1. 72.1. 22.6. 5.3. 6.7. 34.6. ... 0.4556. 0.4408. 0.5739. tune. 0.4903. 0.4639. 0.6000. 0.4567. 0.4493. 0.5652. Table 20: Cumulative Improvements on TREC-7 without wp.
  12. A learned emotion space for emotion recognition and emotive speech…

    mi.eng.cam.ac.uk/UKSpeech2017/posters/z_hodari_poster.pdf
    23 Dec 2017: Non-emotive 5.845 0.329 52.846 14.768. Listening test. • MUSHRA listening test, 16 screens, 20 participants• Copy synthesis reference: 100 rating for all samples.
  13. The Cambridge University Multimedia Document RetrievalDemo System…

    mi.eng.cam.ac.uk/reports/svr-ftp/tuerk_sigir00demo.pdf
    3 May 2000: On the Internet audio used herethe run-time is increased due to reduced audio qualitybut the general level of transcription accuracy remainshigh at approximately 20% word error rate on NPR data.
  14. The Cambridge Multimedia Document Retrieval (MDR) Project : Summary…

    mi.eng.cam.ac.uk/reports/full_html/sparckjones_cltr517.html/
    10 Oct 2001: 20 40.90 32.97 38.65 41.45 39.05 36.22 BE DBRF3 (X) 65.42 65.04 45.12 42.50. ... t=200 r=20, tf=0.5 (same as T8) X: For Trec-8 -> Nov 96 to Jan 98 (pre-trec-8) = 60,000 stories (129614 terms).
  15. Automatic Telephone Voice Analysis and TherapyLadan Baghai-Ravary and …

    mi.eng.cam.ac.uk/UKSpeech2017/posters/l_baghai-ravary_poster.pdf
    24 Jan 2018: The measures include:. CalibrationThe VoiScan parameters for an individual can be compared with population statistics which have been calculated from 20,000 telephone calls in 12 countries.
  16. Kim et al.: 2003 CU-HTK BN-E Systems 2003 CU-HTK ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/kim_rt03s.pdf
    24 Jul 2003: 14.5%. 13.8%. MPE MPEMAPMLE HLDA. 18.0. 16.0. 14.0. 20.0. WER(%)VarMix/LatticeRegen. %WER on BNeval98. ... 16.0. 14.0. 20.0. WER(%). 14.4%. 14.9%. 1998 trigram. VarMix/LatticeRegen. %WER of various acoustic models on BNdev03.
  17. Evermann, Kim, Wang, Woodland et al.: CU-HTK Fast System ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/evermann_rt03s.pdf
    23 Jun 2003: cluster of IBM x335 dual Xeons– SunGrid batch queuing system (400k jobs since Nov’02)– for eval runs: keep all data local, use 20 fastest single CPUs (2.8GHz). ... 0 26.1 23.7P3.3-cn 20.4 24.3 26.6 24.0final 19.9 23.5 25.8 23.3.
  18. 13 May 2010: effect very similar to that observed with non-axially aligned,elliptical inclusions [20, 21]. ... This is very likely the “fillin” effect [20, 21]. 6. (a) 10 mm 0.
  19. The Development of the Cambridge UniversityRT-04 Diarisation System…

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tranter_rt04.pdf
    15 Feb 2005: sorting didev03 eval03 sttdev04 dev04f2 devallnone 18.0 15.9 21.2 26.9 20.3time 17.5 16.7 21.5 25.7 20.2spkr-start 17.5 17.9 ... 18.5. 19. 19.5. 20. mea. n D. ER. on. all. 24 d.
  20. Progress in English Conversational TelephoneSpeech Transcription Khe…

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/sim_sttmar05.pdf
    12 Apr 2005: S6 15K (36) 32.1 24.3 28.3 24.3. S1 6K (28)8. 27.9 20.2 24.2 20.5S4 9K (36) 26.8 19.5 23.3 ... S4—. 826.7 19.6 23.3 20.0. 9K 26.3 18.9 22.7 19.4. S6 — 8 26.5 19.4 23.0 19.5.
  21. Recent Improvementsin the CUED CTS SU System M. Tomalin ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tomalin_mar05mde.pdf
    28 Apr 2005: 20.4 %: before co-ordinating conjunctionEx: that’s unbiased honesty () but then again. ... 20.4 %: before potential Discourse MarkerEx: on the other hand well by telling the truth.
  22. Diarisation Research at CUED Sue Tranter and Srinivasan Umesh ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tranter_mdetechmay04.pdf
    29 Apr 2004: Appendix - Cluster Voting Results by Show. System ABC VOA PRI NBC CNN MNB TOTALCUED-diary-bic (input 1) 32.03 20.78 21.40 32.06 37.92 10.74 ... 12CUED-diary-cost (input 2) 29.26 19.82 20.48 31.56 37.18 29.34 27.09Best CVOS score 26.71 18.43 18.11 29.84 37
  23. GLOBAL OPTIMISATION OF NEURAL NETWORK MODELSVIA SEQUENTIAL…

    mi.eng.cam.ac.uk/reports/svr-ftp/freitas_icslp98.pdf
    10 Apr 2000: The results are shown in Figure 6. 0 10 20 30 40 50 60 70 80 90 100. ... 5. 5.2. 5.4. 5.6. 5.8. 6. Tra. inin. g. 0 10 20 30 40 50 60 70 80 90 100.
  24. INVESTIGATION OF ACOUSTIC MODELING TECHNIQUES FOR LVCSR SYSTEMS X. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/liu_icassp2005.pdf
    19 May 2005: The finalerror rates were 20.5% on eval03 and 16.9% on dev04. ... P3aP3c 23.9 16.8 20.5 16.9. Table 1. CTS 10xRT system baseline performance.
  25. 13 May 2010: 1. 2.5. (f) (g) 0. 10. 20. Pixel. 0. 63. Str.
  26. Reconstruction and Motion Estimation fromApparent Contours under…

    mi.eng.cam.ac.uk/reports/svr-ftp/wong_bmvc99.pdf
    30 Jan 2000: The apparentcontoursweretracked by usingcubic B-splinesnakes[4](seefig. 2). Fundamentalmatrices[13, 20] betweentwo successive imageswereformedfrom thecorrespondingprojectionmatricesandcorrespondenceswerethenfoundby solv-ing for ... IEEE
  27. Woodland et al.: English CTS Systems 2003 CU-HTK English ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/woodland_rt03s.pdf
    24 Jul 2003: 7HLDA pruned bg 20.0 34.4 34.0 29.4MPElattice regen/comb 19.4 34.0 33.6 28.9. % ... Cambridge UniversityEngineering Department. Rich Transcription Workshop 2003 20. Woodland et al.: English CTS Systems.
  28. Visual gesture variability between talkers in con4nuous visual speech …

    mi.eng.cam.ac.uk/UKSpeech2017/posters/h_bear_poster1.pdf
    23 Dec 2017: 2. 4. 6. 8. 10. 12. 14. 16. 18. 20. M2(2,2). ... 2. 4. 6. 8. 10. 12. 14. 16. 18. 20. M7(7,7).
  29. CU-HTK April 2002 Switchboard System Phil Woodland, Gunnar Evermann,…

    mi.eng.cam.ac.uk/reports/svr-ftp/woodland_rt02.pdf
    5 Jun 2002: 16 20 24 2833. 33.5. 34. 34.5. 35. 35.5. 36. 36.5. ... Transformsare not updated (ML-SAT transforms). Cambridge UniversityEngineering Department. Rich Transcription Workshop 2002 20.
  30. CU-HTK March 2001 Hub5 system Phil Woodland, Thomas Hain, ...

    mi.eng.cam.ac.uk/reports/svr-ftp/woodland_lvcsr01.pdf
    31 May 2001: eval98 40 sides Swbd2 (eval98-swbd2), 40 sides of CHE (eval98-che). eval97sub 20 side subset of eval97 evaluation set (Swbd2 CHE). ... Hub5 Workshop 20. Woodland, Hain, Evermann & Povey: CU-HTK March 2001 Hub5 system.
  31. TWO-WAY CLUSTER VOTING TO IMPROVE SPEAKER DIARISATION PERFORMANCE S.…

    mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp05.pdf
    25 Mar 2005: 63 20.78 21.15 32.06 37.18 10.74 25.19EP 15mix 30.30 19.27 18.11 29.84 37.18 10.74 23.48. ... 34 18.21 12.06 30.78 33.62 8.99 21.54EP 16mix 27.01 19.66 10.45 26.88 33.62 8.99 20.33.
  32. paper.dvi

    mi.eng.cam.ac.uk/reports/svr-ftp/liu_icassp2004.pdf
    29 May 2004: Gauss 24.0 20.7 20.7 17.7 16.0WER (%) 35.3 35.1 35.2 35.3 35.5. ... Using the “opti-mal” structure, determined with α = 0 and 4 iterations of structureoptimization the error rate fell to 35.1% and the average numberof components per state was 20.7.
  33. A Statistical Consistency Check for the SpaceCarving Algorithm. A. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/broadhurst_cipolla_bmvc2000.pdf
    25 Oct 2000: The imageswere capturedusing a Fuji-700 digital camera,and about 20-30 pointcorrespondenceswereenteredmanually. The imageswereprojectively calibratedusing[3], and were then upgradedto a metric calibration using [7]. ... Notice how the
  34. Experiments with Fisher Data Gunnar Evermann, Bin Jia, Kai ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/evermann_sttmay04.pdf
    25 May 2004: Gaussianisation. • Transform any distribution to standard Gaussian N(0, I). 20 15 10 5 0 5 10 15 200. ... Gaussianised 29.8 21.9 26.0CN 28.7 21.3 25.1. CNC 28.1 20.8 24.6. •
  35. THE 1998 HTK SYSTEM FOR TRANSCRIPTION OFCONVERSATIONAL TELEPHONE…

    mi.eng.cam.ac.uk/reports/svr-ftp/hain_icassp99.pdf
    27 Sep 2000: The worderror rate obtained is almost 20% better than our 1997 system onthe development set. ... The eval97sub set was used forsystem development and consisted of 20 conversation sides fromSwbd-II and CHE.
  36. On Person Authentication by Fusing Visual and Thermal Face ...

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_AVSS06.pdf
    1 Sep 2006: a) Glasses ON. 0 20 40 60 80 100 1200.85. 0.9. ... Shashua. Learning over sets using kernel principalangles.JMLR, 4(10), 2003. [20] L.
  37. Model Refinementfr om Planar Parallax A. R. Dick R. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/dick_bmvc99.pdf
    5 Dec 2003: 17] T. Vieville, C. Zeller, andL. Robert. Using collineationsto computemotion andstructurein an uncali-bratedimagesequence.International Journal of Computer Vision, 20(3):213–242,1996.
  38. Ongoing Experiments with Fisher Data Ricky Chan, Gunnar Evermann ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/chan_stthomas03.pdf
    10 Dec 2003: 25.2 29.5 20.6 26.8 23.5. ... New LMs: Eval03 with CU-HTK P1-P2 System. Overall Swbd Fisher Male Femaleh5train03b LM03 24.6 28.7 20.2 25.7 23.5h5train03b LM03Fi 23.9 28.2
  39. Structure and Motion from Silhouettes Kwan-Yee K. Wong and ...

    mi.eng.cam.ac.uk/reports/svr-ftp/wong_iccv01.pdf
    19 Apr 2001: Wewould also like to extend the system to recover surface re-flectance [8, 20], so as to produce photo-realistic 3D modelsunder different lighting conditions. ... IEEE Trans. on Pattern Analysis and Machine In-tell., 20(10):1091–1096, Oct 1998.
  40. Optimisation of Fast LVCSR Systems Gunnar Evermann, Phil Woodland ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/evermann_stthomas03.pdf
    10 Dec 2003: 10. 20. 30. 40. 50. 60. 10 20 30 40 50 60.
  41. The 1998 HTK Broadcast News Transcription System:Development and…

    mi.eng.cam.ac.uk/reports/svr-ftp/woodland_darpa99.pdf
    8 Mar 2000: Y 14.2 8.0 15.4 20.3 16.5 14.0 16.6 24.6. ... ROVER fgintcat 4/Y1/N 13.8 7.8 15.1 20.1 15.8 13.6 16.6 24.1.
  42. Discriminative Adaptation & Adaptive Training Lan Wang & Phil …

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/wang_stthomas03.pdf
    10 Dec 2003: 28.6MPE 20.2 33.0 32.7 28.6MPE-SAT(MPE CDLT) 20.1 31.8 31.8 27.8. ... MPE-based DLT converges fast. EARS STT meeting Dec’03 20. Wang & Woodland: Discriminative Adaptation & Adaptive Training.
  43. Metadata Extraction at Cambridge University Sue Tranter, Marcus…

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tranter_earsjan03.pdf
    8 Jul 2003: sub 2.2 3.4 12.6 10.9 0.5 20.4 28.5 29.10cu-stt2 1.4 7.4 20.0 6.2 0.8 12.6 ... SU Results - changing N. 0 0.5 1 1.5 20.6. 0.7.
  44. THE CAMBRIDGE UNIVERSITY SPOKEN DOCUMENT RETRIEVAL SYSTEM S.E.…

    mi.eng.cam.ac.uk/reports/svr-ftp/johnson_icassp99.pdf
    8 Mar 2000: Unstopped Term Error. Unstopped Word Error. 20 25 30 35 40 45 5020. ... 0 10 20 30 40 50 60 700.52. 0.54. 0.56. 0.58.
  45. Advances in Structural Metadata for RT-04 atCUED M. Tomalin ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tomalin_rt04.pdf
    15 Feb 2005: 0/56.8 29.2/15.7/56.2. PFMctsrt04 cl40-tg 33.1/20.3/63.9 33.3/18.7/62.6 30.8/19.7/61.9. ... Cambridge University RT-04 workshop: November 2004 20. Tomalin and Woodland: Advances in Structural Metadata for RT-04 at CUED.
  46. Face Set Classification using Maximally Probable Mutual Modes Ognjen…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ICPR06.pdf
    29 Apr 2006: λ(1)Dj = λ(2)Dj. (19). Then, writing. |Ci| =D. j=1. λ(i)j , (20). ... 12] K. K. Sung and T. Poggio. Example-based learning for view-basedhuman face detection.PAMI, 20(1), 1998.
  47. C:/SFWDoc/Academic/Publications/2006/ICPR_2006/Final_ContGest/icpr_200…

    mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_icpr06a.pdf
    21 Sep 2006: 20.2 fps).Figure 3 illustrates the recognition process on a typical test-ing clip. ... Pentland. Real-time ameri-can sign language recognition using desk and wearable com-puter based video.PAMI, 20(12):1371–1375, 1998.
  48. Structural Metadata at CUED: Progress Report Marcus Tomalin, Sue ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tomalin_earsmay03.pdf
    24 Jul 2003: 40cl-bg 28.3 40 N/A40cl-tg 31.4 40 N/A. bg 40cl-bg 27.7 40 0.3, 0.7tg 40cl-tg 20.8 40 0.9, ... 41 15.20 70.54.
  49. SU Detection for RT-03f at Cambridge University Marcus Tomalin, ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tomalin_rt03f.pdf
    20 Nov 2003: 20. 30. 40. 50. 60. 70. 80. SU. %E. RR. suevalv12 suevalv15 rtevalv2.3a b c d e f g a b c d e f g a b c d ... RT-03f Workshop 13th November 2003 20. Tomalin et al.: SU Detection for RT-03f at Cambridge University.
  50. 4 BEAR, TAYLOR: VISUAL SPEECH RECOGNITION: A MINI REVIEW ...

    mi.eng.cam.ac.uk/UKSpeech2017/posters/h_bear_poster2.pdf
    23 Dec 2017: The most common published figures are correctness andaccuracy as shown in Equations 1 and 2 respectively [20]. ... 0 20 4 17 0 1 2 0 0 1 0 0 1 0 0 03 6 6 163 3 7 7 2 8 7 1 4 2 0 14 2
  51. ADAPTATION OF PRECISION MATRIX MODELS ON LARGE VOCABULARYCONTINUOUS…

    mi.eng.cam.ac.uk/reports/svr-ftp/sim_icassp2005.pdf
    12 Apr 2005: DIAGC mllr 10.7 13.2 20.0. SPAMmllr+ 10.6 13.1 19.5mllr 10.6 13.1 19.5. ... gender dependent (GD) DIAGC system was chosen as the base-line. This system gave WERs of 10.7%, 13.2% and 20.0% on thethree test sets.

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