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  1. Results that match 1 of 2 words

  2. 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
  3. 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
  4. 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.
  5. 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.
  6. 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.
  7. Experiments in Broadcast News Transcription

    mi.eng.cam.ac.uk/reports/full_html/woodland_icassp98.html/
    1 Mar 2000: 24.4. F5. 28.6. 23.8. 27.1. 26.5. FX. 58.5. 55.2. 56.8. 55.0. ... 39.6. 25.1. 37.2. F4. 24.1. 24.7. 24.5. 22.6. F5. 27.6. 25.8.
  8. 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.
  9. 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.
  10. 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
  11. Spoken Document Retrieval for TREC-7 at Cambridge University

    mi.eng.cam.ac.uk/reports/full_html/johnson_trec7.html/
    30 Mar 2000: This system gave a word error rate of 24.1% on the TREC-6 test data. ... map. stop. stem. CUHTK. 24.8. 25.0. 24.9. 22.8. 22.3. Dragon. 29.8.

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