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  2. Two-way Cluster Voting to Improve Speaker Diarisation Performance

    mi.eng.cam.ac.uk/reports/full_html/tranter_icassp05.html/
    31 Mar 2005: 20.78. 19.15. 32.06. 37.18. 10.74. 24.52. † St. 128mix. 27.66. 20.78. ... 19.86. 11.78. 20.37. 22.77. 12.28. 18.10. † St. 128mix. 26.34. 18.21.
  3. 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.
  4. 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.
  5. The Development of the Cambridge University RT-04 Diarisation System

    mi.eng.cam.ac.uk/reports/full_html/tranter_rt04.html/
    10 Jan 2005: 22.4. 20.2. PLP. Y. -. Y. 25.4. 19.3. 27.9. 24.1. 24.3. ... 16.9. 17.8. 24.6. 24.0. 20.9 @ 2521. 10. 10. 19.9. 21.3.
  6. The Cambridge University March 2005 Speaker Diarisation System

    mi.eng.cam.ac.uk/reports/full_html/sinha_eurospeech05.html/
    22 Sep 2005: B D. models were formed by performing a single iteration of (mean-only) MAP adaptation, with τ =20 from the. ... IAC. DataSet. MS/FA/SPE/DER. Cluster Imp. Seg Imp. Base. Dev24. 1.2/1.1/17.9/20.17. 6.59@718.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. Recent Improvements in the CUED DiarisationSystem Sue Tranter, Rohit…

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/tranter_mar05mde.pdf
    26 Mar 2005: 0 constant 19.1 17.1 (17.1)3 Concat. 0 BIC 18.9 20.3 (16.8)4 Concat. ... MDE Technical Meeting, March 2005 20. Tranter et al.: Recent Improvements in the CUED Diarisation System.
  12. Recent Developments at Cambridgein Broadcast News Transcription D.Y.…

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/kim_rt04.pdf
    15 Feb 2005: Cambridge UniversityEngineering Department. RT04 EARS workshop 20. Recent Developments at Cambridge in Broadcast News Transcription. ... 0.16 0.18 0.2 0.22 0.24 0.2612. 14. 16. 18. 20. 22.
  13. A NOVEL SELF-ORGANISING SPEECH PRODUCTIONSYSTEM USING…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/blackburn_ICPhS95.pdf
    9 Aug 2005: 10 20 30 40 50 60 703.5. 3. 2.5. 2. 1.5. ... 0 20 40 60 80 1000. 8000. Speech frame index (10msec increments).
  14. 9 Aug 2005: 0. 0.1. 0.2Speech Segment. 0 5 10 15 20 25 302. ... 0 5 10 15 20 25 302. 1.5. 1. 0.5. 0.
  15. Face Recognition from Face Motion Manifolds using Robust…

    mi.eng.cam.ac.uk/reports/svr-ftp/oa214_FPIV_2004_paper1.pdf
    8 Aug 2005: 5. 10. 15. 20. 25. 30. 35. 5 10 15 20 25 30 35. ... 20] W. S. Yambor. Analysis of PCA-based and fisherdiscriminant-based image recognition algorithms.
  16. THE USE OF RECURRENT NEURAL NETWORKSFOR CLASSIFICATION T. L. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/burrows_nnsp94.pdf
    9 Aug 2005: 20 40 60 80 100 120 140 1601. 0.5. 0. 0.5. ... 1. Am. plit. ud. e. b) Hidden Node Outputs. 20 40 60 80 100 120 140 1601.5.
  17. The Cambridge University March 2005 Speaker Diarisation System R. ...

    mi.eng.cam.ac.uk/reports/full_html/sinha_eurospeech05.html/paper.pdf
    22 Sep 2005: only) MAPadaptation, withτ = 20 from theB models to theD data. ... IAC DataSetMS/FA/SPE/DER Cluster Imp Seg ImpBase Dev24 1.2/1.1/17.9/20.176.59@718 4.36@2363Base Eval
  18. 16 Sep 2005: Ultrasound in Medicine & Biology, 20(9):923–936, 1994. [5] A. Fenster, D. ... IEEE Transactions on Medical Imaging, 17(5):681–693, 1998. [20] A. State, D.
  19. 9 Aug 2005: number of times we would expect to see4. in7[. is. 0 2#4?5@7>.,8 : -)0;2#4D5N7>.,8/L 27>.,8 (20)Assuming words to occur independently within each
  20. CLASSIFICATION USING HIERARCHICALMIXTURES OF EXPERTS S.R.Waterhouse…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/waterhouse_hme.pdf
    9 Aug 2005: In particular we use a 40-20-40 thresholdcriterion which dictates that an output is only correct if it is greater than 0. ... Back-propagation networks have been used to solvethe problem [12] using a 2-5-5-1 network with shortcut connections between
  21. A Modular Q-Learning Architecture for Manipulator Task Decomposition…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/tham_ml94.pdf
    9 Aug 2005: 010. 2030. 40. 0. 10. 20. 30. 40-0.2. 0. 0.2. 0.4. ... 010. 2030. 40. 0. 10. 20. 30. 40-0.6. -0.4. -0.2. 0.
  22. THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY RT-04 DIARISATION SYSTEM…

    mi.eng.cam.ac.uk/reports/full_html/tranter_rt04.html/paper.pdf
    10 Jan 2005: 19.7spkr-mid 16.7 16.2 23.5 23.5 20.0. ... 40 45 50 55 60 6517.5. 18. 18.5. 19. 19.5. 20.
  23. Contour-Based Learning for Object Detection Jamie ShottonDepartment…

    mi.eng.cam.ac.uk/reports/svr-ftp/shotton_iccv05.pdf
    8 Aug 2005: 0 10 20 30 40 50. 0.5. 0.6. 0.7. 0.8. 0.9. ... Cipolla. Filteringusing a tree-based estimator. In ICCV03, pages 1063–1070, 2003. [20] J.
  24. Face Recognition with Image Sets Using Manifold Density Divergence ...

    mi.eng.cam.ac.uk/reports/svr-ftp/oa214_CVPR_2005_paper1.pdf
    8 Aug 2005: 01. 20. 24. 2.5. 2. 1.5. 1. 0.5. 0. 0.5. 1. ... IEEE Conference on Computer Vision and PatternRecognition, pages 313–320, 2003. [20] B.
  25. 9 Aug 2005: o o;jWvi dUi! ikd. 0 10 20 30 40 50 60 70 80 90-20. ... º> QZ "º>. , //6 7 12;" 8[x'USz:% 6Q / & x 1435 69 x /Y3 F 20 - /UX.
  26. 9 Aug 2005: 10P,= 6 ,Bx| ,=) &,G9o10PB4;,=)20 & &|0S)? ,=E7 C7? 9-x7B ,=q ,W M,G9,W H| Ux77E7 &,Bw!@71(B7 @,=0 & & B4F &S. ... tÖSÉ t Ñ0ÊEÑ&%;Ñ0Ê'#. ( )( ). -100-50. 050. 100. 0. 20. 40. 60. 80. 1002. 4. 6.
  27. A Face Recognition System for Access Control using Video ...

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_PR06.pdf
    21 Dec 2005: pus of video sequences of faces in random motion. To learn the model, we took 20. ... For offline learning of illumination subspaces we used 10s video sequences of 20.
  28. 9 Aug 2005: 0.8. 1. x. y(x). 0 20. 0.02. 0.04. 0.06. 0.08. x. ... y(x. )f(x. ))2. 0 20. 0.2. 0.4. 0.6. 0.8. 1. x.
  29. Sparse Finite Element Level-Sets for Anisotropic Boundary Detection…

    mi.eng.cam.ac.uk/reports/svr-ftp/weber_scaleSpace2005.pdf
    24 May 2005: However, the methodology of [13] is not confined to standardsimplices. Here, we obtain a convenient partitioning M of space as Delaunaytetrahedrisation [20] of the vertex-set (2 Z3).
  30. 9 Aug 2005: 4 5. #. 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.20.
  31. TPAMI0110-0304-1 1..13

    mi.eng.cam.ac.uk/reports/svr-ftp/williams_pami2005.pdf
    20 Apr 2005: the same number of data).Fig. 20 shows the mean CPU utilization of each algorithm. ... 20, no. 10, pp. 1025-1039, Oct. 1998. [11] M. Isard and A.
  32. STRUCTURAL METADATA RESEARCH IN THE EARS PROGRAM Yang Liu1,5 ...

    mi.eng.cam.ac.uk/reports/svr-ftp/tomalin_icassp05.pdf
    12 May 2005: Additionally, textual information is. 1 2 5 10 20 40 60 80 90 1. ... Woodland, “SU detection forRT-03F at Cambridge University,” http://www.nist.gov/speech/tests/rt/rt2003/fall/presentations/, 2003. [20] Y.
  33. Learning New Articulator Trajectories for a Speech Production…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/blackburn_icnn95.pdf
    9 Aug 2005: 0 10 20 30 40 50 60 70 80 90 100.
  34. Edge tracking for motion segmentation anddepth ordering P. Smith, ...

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/smith_bmvc1999.pdf
    9 Aug 2005: The EM iteration process is repeated until convergence (i.e. until there is no significantchange in probabilities), or for 20 iterations.
  35. 9 Aug 2005: 0. 20. 40. 60. 1000 2000 3000 4000. (Hz). (dB). LP(26) Residual. ... 20. 40. 60. 80. 1000 2000 3000 4000. (Hz). (dB). NLP(10-2) Residual Spectrum.
  36. Sensor Fusion and Occlusion Refinement for Tablet-based AR Georg ...

    mi.eng.cam.ac.uk/reports/svr-ftp/klein04tablet.pdf
    18 Jan 2005: To aid readabil-ity the notation here is loosely based on Welch and Bishop’sexcellent tutorial [20] on the filter. ... 20] G. Welch and G. Bishop. An introduction to the kalman fil-ter.
  37. Epipolar Geometry from Profiles under Circular Motion Paulo R. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/mendonca_PAMI.pdf
    9 Aug 2005: Typical values. 20. of lie between -0.5 rad and 0.5 rad, or and. ... perspective projection. Int. Journal of Computer Vision, 31(1):31–50, February 1999. [20] T.
  38. Desired Utterance Text Extraction of desiredphoneme string andF0…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/tuerk_eurospeech93a.pdf
    9 Aug 2005: 09KP B=>#"E UQ9! #EK6O! 0O;"H! (,."I64cc7[V /! 6 =>##D"ELU'. "EK.]. #20 S }B 0l):! ... Nodes 34-43 Position features. Input Vector. Output vector: Node 0 Probability of VoicingNode 1 RMS energyNodes 2-22 20 Cepstral Coefficients.
  39. SENSORLESS FREEHAND 3DULTRASOUND IN REAL TISSUE: SPECKLE…

    mi.eng.cam.ac.uk/reports/svr-ftp/gee_tr510.pdf
    10 Jan 2005: Even if a practical speckle detector were able to singleout these two patches, we would still have residual distance errors of around 20–30%, and, withjust two offsets, we would be ... Though much improved, the results stillindicate errors of around
  40. 9 Aug 2005: Linear moments method. Buffon transform method. Proposed method. 0 5 10 15 20 25 30 35 4020. ... Buffon transform method. Proposed method. 0 10 20 30 40 50 60 70 80 9020.
  41. University of Cambridge, 3D Ultrasound Research Sequential 3D…

    mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/3dus_tutorial.pdf
    9 Aug 2005: Sequential 3D Diagnostic Ultrasound using the Stradx System 20. Using voxel arrays. ... In Proceedings of Medical Image Understanding andAnalysis, pages 17–20, Oxford, UK, 1999.
  42. 9 Aug 2005: $#%#&"'$#%"()!#%" #% ,. 15 20 25 30 35 40 45 50 55 6025. ... 20. 15. 10. 5. 0. 5. 10Initial projection step. first eigenvector depending on τ.
  43. 9 Aug 2005: 600. 700. 800. 900. 1000. 0 10 20 30 40 50 60 70 80 90 100. ... 40. -20. 0. 20. 40. 60. 80. 100. 500 1000 1500 2000 2500 3000 3500 4000.
  44. 3D ELASTOGRAPHYUSING FREEHAND ULTRASOUND J. E. Lindop, G. M. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/lindop_tr531.pdf
    28 Jul 2005: 20]. Models developed by Varghese et al. incorporatedthe effects of electronic noise and signal decorrelation due to axial strain, and they predictedpassbands at 1–10% strain. ... 1G 0.8370 -0.29 1B 0.6250 -0.12. 2G 0.8581 -0.12 2B 0.3641 0.20.
  45. 9 Aug 2005: Ï. 0 1000 2000 3000 4000 5000 6000 7000 800040. 30. 20.
  46. 9 Aug 2005: 24350. 510. 1520. 2530. 0. 10. 20. 300.8. 0.6. 0.4. 0.2. ... TF. L. P( R)P(R). 0.85 0.150.20 0.80. TF. R. virtualnode. A.
  47. Estimating Disparity and Occlusions in Stereo Video Sequences Oliver…

    mi.eng.cam.ac.uk/reports/svr-ftp/williams_cvpr2005.pdf
    9 Aug 2005: 20] J. Sun, H.-Y. Shum, and N.-N. Zheng. Stereo matching usingbelief propagation.
  48. 9 Aug 2005: 0 ". ||||zxkxB3x! L x z ||||Zy{ kxK|z! L x z {. RE OEi G0)# Ai'# 20 LE( AFE2 OEiE! L[L[A# 0:O)0:.#7. e-. ... B#A#0 W 0:57'?20:;r 0'! 6!6! /E # /(6'O. 2A;6; D@"Ri! 6p g.
  49. 9 Aug 2005: 0 5 10 15 20 2572. 74. 76. 78. 80. 82.
  50. 9 Aug 2005: 0. 20. 40. 60. Distance monitor along sentence for male and female speaker.
  51. 9 Aug 2005: 3. 0 10 20 30 40 50 60 70 80 90 1000. ... Consider the first term on the right-hand side of (19) :. X KI I 0 I j X 4 KI I 0 6 j X K I j X (20).

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