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1 - 10 of 40 search results for katalk:za33 24 |u:mi.eng.cam.ac.uk where 0 match all words and 40 match some words.

  1. Results that match 1 of 2 words

  2. LARGE SCALE DISCRIMINATIVE TRAINING FORSPEECH RECOGNITION P.C.…

    mi.eng.cam.ac.uk/reports/svr-ftp/woodland_asr00.pdf
    6 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

  3. Class-based language model adaptation using mixtures of word-class…

    mi.eng.cam.ac.uk/reports/full_html/moore_icslp00.html/
    2 Nov 2000: 225.85. 192.66. 224.24. 187.37. 1003. 250. 158.98. 151.15. 158.68. 149.37.

  4. 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

  5. A Statistical Consistency Check for the SpaceCarving Algorithm. A. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/broadhurst_cipolla_bmvc2000.pdf
    25 Oct 2000: Figure 2: Resultsfrom the existing SpaceCarving algorithm using different thresholdsettings. The voxel array size was , and the thresholdswere 48,32,24,16(of 255)respectively. ... Figure 4: Resultsfrom the existing SpaceCarving algorithm using different

  6. The Applications of Uncalibrated Occlusion Junctions A.…

    mi.eng.cam.ac.uk/reports/svr-ftp/broadhurst_cipolla_bmvc1999.pdf
    25 Oct 2000: 7] M.A. FischlerandR.C.Bolles.Randomsampleconsensus:A paradigmfor modelfitting with applicationsto imageanalysisandautomatedcartography. CACM, 24(6):381–395,June1981. [8] R.I.

  7. ITERATIVE UNSUPERVISED ADAPTATION USING MAXIMUMLIKELIHOOD LINEAR…

    mi.eng.cam.ac.uk/reports/svr-ftp/woodland_icslp96.pdf
    17 Oct 2000: 704/c 26.3 15.570a/b 10.3 1.970f/d 18.8 7.670w/c 24.2 15.8. Table 1: Lattice error rates for several development test speakerswith ... a fg 14.24 —HMM-2 thresh. b fg 13.81 —HMM-2 thresh. c fg 13.71 6.68.

  8. LARGE SCALE MMIE TRAINING FOR CONVERSATIONAL TELEPHONE SPEECH…

    mi.eng.cam.ac.uk/reports/full_html/woodland_stw00.html/
    5 Oct 2000: The bigram 1-best hypotheses had a 24.6% word error rate (WER) and a Lattice WER (LWER) of 6.2%...

  9. LARGE SCALE MMIE TRAINING FOR CONVERSATIONALTELEPHONE SPEECH…

    mi.eng.cam.ac.uk/reports/svr-ftp/woodland_stw00.pdf
    5 Oct 2000: Lattices were generated on the training set using a bigramLM. The bigram 1-best hypotheses had a 24.6% word error rate(WER) and a Lattice WER (LWER) of 6.2%.

  10. 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.

  11. Pronunciation modeling by sharing Gaussians

    mi.eng.cam.ac.uk/reports/svr-ftp/nock_csl00.pdf
    31 Jul 2000: 0885–2308/00/020137 24 $35.00/0 c 2000 Academic Press. 138 M. Saraçlaret al.

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