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  1. Results that match 1 of 2 words

  2. A LANGUAGE SPACE REPRESENTATION FOR SPEECH RECOGNITION

    mi.eng.cam.ac.uk/~mjfg/icassp15-ragni.pdf
    18 May 2015: There are many options to select the form of rep-resentation of the clusters and the combination method to employ[18, 17, 13, 24, 25]. ... 20, no. 6, pp. 1713–1724, 2012. [24] V. Diakoloukas and V.
  3. 20 Feb 2018: The COMMUNICATOR systems in contrast onlyrequest between 24% and 43% of the unknown slots in each state.
  4. 13 Aug 2008: In common with other work in this. 5. area [9, 24], G is approximated by the diagonalised empirical covariance matrix of the trainingdata. ... 00 25.48 21.73 25.95 24.46 21.64 26.05 24.51 22.56.
  5. 27 Jul 2020: CBCT non-planarity 2.47 2.46 3.35 15.7 16.0 14.8 12.1 10.8 8.63reach 9.36 9.16 9.57 26.7 24.7 ... MDCT non-planarity 3.04 3.67 4.52 15.1 14.2 15.5 11.7 10.6 8.3reach 13.6 11.2 10.4 26.3 24.1
  6. Paper8-CV-intro.dvi

    mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/2024-IB-Paper8-CV-Introduction.pdf
    1 May 2024: 2D array I(x,y,t) incomputer memory. CCD. • A typical digital SLR CCD measures about 24 16 mm.
  7. 11 Mar 2016: MPE— 7.15 11.06 14.37 24.54 16.79CML 6.95 11.00 14.29 24.39 16.68large-margin 7.02 10.92 14.16 24.28 ... Therefore the systems use graphemic lex-ica generated using an approach which is applicable to all Unicodecharacters [24].
  8. Towards Learning Orientated Assessment for Non-native Learner Spoken…

    mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/ALTA_Sheffield_20190306.pdf
    21 Feb 2022: 300 300. 25.5. 400 24.5. 400 24.4. ASR on Non-native Speech (2). • ... Thai dh d 7.24 oh aa 5.21. 30. • Top 2 recurrent substitution errors for speakers in each L1.
  9. DEVELOPMENT OF THE 2003 CU-HTK CONVERSATIONAL TELEPHONE…

    mi.eng.cam.ac.uk/reports/svr-ftp/evermann_icassp2004.pdf
    27 May 2004: purpose WER. P1 supervision for VTLN 34.2P2 supervision for MLLR 28.4P3 lattice generation 24.8. ... System (P4) A B C DSAT HLDA SPron non-HLDA23.0 23.6 23.4 24.8.
  10. lect1.dvi

    mi.eng.cam.ac.uk/~mjfg/local/4F10/lect1.pdf
    10 Nov 2015: for minimum error with generative models. 24 Engineering Part IIB: Module 4F10 Statistical Pattern Processing.
  11. 13 Jun 2013: Ney LM with optimized discounting parameters [24] usinga modified version of the RWTH open source decoder [25]; and (6)DBN, a deep belief network hybrid model [26, 27] with discrimi-native ... Ney, “Posterior-scaled mpe: Novel discriminative
  12. 20 Feb 2018: In this section, a Gaussianprocess-based reward estimator is described which uses active learning tolimit intrusive requests for feedback and a noise model to mitigate the effectsof inaccurate feedback [24]. ... 24. Figure 13: The number of times each
  13. 3_2_ransac

    mi.eng.cam.ac.uk/~cipolla/lectures/4F12/Slides/4F12-ImageStitching.pdf
    27 Oct 2020: x̃2 = [ R2 | 0 ] X̃ = R2X (A.24).
  14. 20 Feb 2018: U| 103 and |M| 103. (24). Goals are composed ofNC constraints taken from theset of constraintsC, andNR requests taken from the setof requestsR.
  15. eps.dis.dur.testa.eps

    mi.eng.cam.ac.uk/~mjfg/gales_ASRU09.pdf
    14 Sep 2010: Using 17 pairs, about 24% of thetotal number of pairs, 92% of the WER improvement usingthe 1-v-1 system over the VTS baseline was achieved.
  16. 20 Feb 2018: The Pietquin model. Train TestPrecision Recall Precision Recall. BIG 19.74 24.11 17.83 21.66LEV 43.11 35.07 37.98 31.57PTQ 45.00 36.35 40.16
  17. main.dvi

    mi.eng.cam.ac.uk/~sjy/papers/ywss05.pdf
    20 Feb 2018: At this point, the dialog state probabilities given by equation 24 are omputed. ... P1. find P2. (a) task 1.0. P1 b=1.0. b=0.7. b=0.3. b=0.24.
  18. Use of Deep Learning in Free Speaking Non-native English Assessment

    mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/TSD2021_Knill.pdf
    21 Feb 2022: 24/56. Deep Density Network-based Grader [1, 7]. • Deep Density Networks predict parameters of a distribution.
  19. Kate Knill ALTA Institute, Cambridge University Engineering…

    mi.eng.cam.ac.uk/~kmk/presentations/Knill_UKSpeech2023_Keynote.pdf
    19 Jun 2023: conversational assessment. 24. Applying Foundation Models to Auto-marking: Neural Text Grader.
  20. 20 Feb 2018: goodbye. ( 1 0.24) you are welcome. goodbye. ( 85 0.19) is there anything else i can help you with?
  21. 20 Feb 2018: THE HIDDEN INFORMATION STATE SYSTEMA block diagram of the HIS system is shown in Figure 13 [23], [24]. ... The history states record grounding and query status information but the details are not relevant here (see [24]).
  22. Machine Intelligence Laboratory

    mi.eng.cam.ac.uk/Main/GMT_EqnSurf
    In the Windows version this will be saved in uncompressed 24-bit.
  23. Roberto Cipolla - Professor of Information Engineering

    mi.eng.cam.ac.uk/~cipolla/publications.htm
    Image and Vision Computing, 24(6):639-647, June 2006. O. Arandjelovic and R.
  24. Abstract for johnson_trec7

    mi.eng.cam.ac.uk/reports/abstracts/johnson_trec7.html
    27 Jul 2020: The broadcast news audio was transcribed using a 2-pass gender-dependent HTK speech recogniser which ran at 50 times real time and gave an overall word error rate of
  25. Royal Society Meeting on Geometry in Computer Vision

    mi.eng.cam.ac.uk/~cipolla/royal_society.html
    28 Nov 2006: Session 3: Grouping and Matching. Thursday 24 July, 09.30-12.30 (Chair: Dr A. ... Session 4: Geometry and Statistics. Thursday 24 July, 14.00-17.40 (Chair: Dr R.
  26. Stradview 7.3

    mi.eng.cam.ac.uk/~gmt11/stradview/versions.htm
    24 Jun 2024: wxWidgets in Linux is still version 3.0.5. 7.24, 1st December 2023.
  27. Abstract for clarkson_icassp97

    mi.eng.cam.ac.uk/reports/abstracts/clarkson_icassp97.html
    27 Jul 2020: Both techniques yield a significant reduction in perplexity over the baseline trigram language model when faced with multi-domain test text, the mixture-based model giving a 24% reduction and the
  28. 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: 0 26.1 23.7P3.3-cn 20.4 24.3 26.6 24.0final 19.9 23.5 25.8 23.3. ... 320xRT 2002† 19.8 24.3 27.0 23.910xRT 2002† 22.3 27.7 31.0 27.2 14%.
  29. Abstract for treece_tr691

    mi.eng.cam.ac.uk/reports/abstracts/biomed/treece_tr691.html
    27 Jul 2020: G.M. Treece and A.H. Gee. 24 April 2014. The local structure of the proximal femoral cortex is of interest since both fracture risk, and the effects of various interventions
  30. Machine Intelligence Laboratory

    mi.eng.cam.ac.uk/Main/GMT_4YP_24_2
    Main > GMT_4YP_24_2. Dr Graham Treece, Department of Engineering.
  31. Professor Steve Young, Publications

    mi.eng.cam.ac.uk/~sjy/publications.html
    P-H. Su, M. Gasic and S. Young (2018). "Reward Estimation for Dialogue Policy Optimisation." Computer Speech and Language, 51(1):24-43. ... B. Thomson and S. Young (2010). "Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems."
  32. paper.dvi

    mi.eng.cam.ac.uk/~mjfg/wang_is2012.pdf
    13 Jun 2013: RVTSJ 14.9 29.6 18.3 43.6 26.6RAT RVTSJ 13.7 28.5 15.0 42.2 24.9.
  33. Roberto Cipolla - Professor of Information Engineering

    mi.eng.cam.ac.uk/~cipolla/publications_all.htm
    Image and Vision Computing, 24(6):639-647, June 2006. O. Arandjelovic and R.
  34. Machine Intelligence Laboratory

    mi.eng.cam.ac.uk/Main/GMTPublications
    Pattern Recognition Letters. Vol. 24, No. 4-5, pp. 705-713, 2003. G. ... Vol. 24, S1, pp. S293-S294, April 2016. T. Turmezei, K. Poole, G Treece.
  35. Improving Retrieval on Imperfect Speech Transcriptions

    mi.eng.cam.ac.uk/reports/full_html/jourlin_sigir99.html/
    8 Mar 2000: HTK. ATT. Dragon. Base1. Sheff. Base2. DERA. WER. 24.8. 31.0. 29.8.
  36. Index of /~cipolla/lectures/PartIB/old

    mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/
    KDTest.zip 24-May-2006 11:00 15K.
  37. The Cambridge University Spoken Document Retrieval System

    mi.eng.cam.ac.uk/reports/full_html/johnson_icassp99.html/
    8 Mar 2000: Sheffield. 39.8. 37.6. 37.1. 34.6. HTK-1. 28.6. 24.9. 24.7. 22.2. HTK-2. ... 24.1. 21.5. 21.2. 18.7. Table 3: Story-based % Word Error Rates for TREC-6 data.
  38. Class-based language model adaptation using mixtures ofword-class…

    mi.eng.cam.ac.uk/reports/svr-ftp/moore_icslp00.pdf
    2 Nov 2000: 1003 250 - 225.85 192.66 224.24 187.371003 250 158.98 151.15 158.68 149.371003 500 - 230.96 193.86 228.93 188.111003 500 159.77
  39. Model-Based 3D Tracking of an Articulated Hand B. Stenger ...

    mi.eng.cam.ac.uk/reports/svr-ftp/stenger_cvpr01.pdf
    12 May 2003: This paper presents a methodfor hand tracking that estimates the pose of a 3D hand modelconstructed from truncated quadrics by using an UnscentedKalman filter [18, 24]. ... Originally published in1952. [24] E. A. Wan and R. van der Merve.
  40. paper.dvi

    mi.eng.cam.ac.uk/~mjfg/wang_icassp13.pdf
    13 Jun 2013: 2011, pp. 24–29, Ieee. [13] M. J. F. Gales and F.
  41. 19 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.
  42. AUTOMATIC COMPLEXITY CONTROL FOR HLDA SYSTEMS X. Liu, M. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/liu_icassp2003.pdf
    19 Sep 2003: Fig. 1. Test set word error rate for all possible models, with thestandard front-end 12, 16 and 24 component performance. ... The best perfor-mance, 36.8%, was obtained using 24 components per state and anHLDA projection from 52 dimensions to 38
  43. 4F12-notes-1.dvi

    mi.eng.cam.ac.uk/~cipolla/lectures/4F12/Slides/4F12-notes-1.pdf
    29 Sep 2023: CCD. • A typical digital SLR CCD measures about 24 16 mm. ... 24 Engineering Part IIB: 4F12 Computer Vision. Further reading. Students looking for a deeper understanding of computer vision might wish to con-sult the following publications, many of
  44. 4F12-notes-4.dvi

    mi.eng.cam.ac.uk/~cipolla/lectures/4F12/Slides/4F12-notes-4.pdf
    2 Nov 2023: 12 p. ′13 p. ′14. p′21 p′22 p. ′23 p. ′24. ... vp24)p22. p′24. . . . . . Z. . . .
  45. Roberto Cipolla - Professor of Information Engineering

    mi.eng.cam.ac.uk/~cipolla/publications_procs.htm
    Professor Roberto Cipolla, Department of Engineering. Conference Proceedings. 2023.. G. Bae, M. de la Gorce, T. Baltrusaitis, C. Hewitt, D. Chen, J. Valentin, R. Cipolla and D. Chen. DigiFace-1M: 1 million digital face images for face recognition.
  46. Two-way Cluster Voting to Improve Speaker Diarisation Performance

    mi.eng.cam.ac.uk/reports/full_html/tranter_icassp05.html/
    31 Mar 2005: full. 30.30. 19.94. 19.15. 32.06. 37.92. 10.74. 24.26. † St. diag. ... full. 24.31. 19.97. 12.75. 19.34. 22.77. 17.50. 19.09. † St. diag.
  47. The 1997 HTK Broadcast News Transcription System

    mi.eng.cam.ac.uk/reports/full_html/woodland_darpa98.html/
    1 Mar 2000: 24.6. F5. 28.6. 23.8. 27.1. 24.8. FX. 58.5. 55.2. 56.8. 55.4. ... 25.3. 29.0. 24.3. 28.1. F2. 38.3. 41.6. 35.7. 37.3. F3. 25.3.
  48. Effects of Out of Vocabulary Words in Spoken Document Retrieval

    mi.eng.cam.ac.uk/reports/full_html/woodland_sigir00.html/
    14 Aug 2000: ID. BASE. BRF. UBRF. 3k. 22.2. 24.4. 33.3. 7k. 33.8. 37.5.
  49. General Query Expansion Techniques for Spoken Document Retrieval

    mi.eng.cam.ac.uk/reports/full_html/jourlin_esca99.html/
    2 Mar 2000: Our retrieval system was run on 7 different sets of automatically transcribed broadcast news texts with a WER varying from 24.8% to 66.2%. ... The overall system gave a WER of 24.8% which corresponded to a Processed Term Error Rate [11] (which more
  50. The 1998 HTK Broadcast News Transcription System: Development and…

    mi.eng.cam.ac.uk/reports/full_html/woodland_darpa99.html/
    2 Mar 2000: F5. 24.4. 23.8. 21.4. 20.0. FX. 32.7. 32.7. 30.9. 30.9. Overall. ... 19.1. 17.2. 24.7. 30.9. P3. bg. 1/N. 19.1. 11.9. 20.4. 27.6.
  51. Machine Intelligence Laboratory

    mi.eng.cam.ac.uk/Main/AHGPublications
    Ultrasound in Medicine and Biology, 24(6):841-854, July 1998. R. Rohling, A. ... Osteoarthritis and Cartilage, 24(S293-S294), April 2016. T.D. Turmezei, A.H. Gee, K.E.S.

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