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1 - 10 of 10 search results for `broadcast news data` |u:mi.eng.cam.ac.uk
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  2. IMPROVING BROADCAST NEWS TRANSCRIPTION BY LIGHTLY…

    mi.eng.cam.ac.uk/reports/svr-ftp/chan_icassp2004.pdf
    27 May 2004: broadcast news data (TDT4 corpus) that were carefully chosen byclosed-caption filtering [3] [7]. ... Finally,conclusions are given in Section 5. 2. ENGLISH BROADCAST NEWS DATA.
  3. EARS STT Overview Phil Woodland February 4th 2004 Cambridge ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/woodland_board_earsfeb04.pdf
    23 Mar 2004: STT Collaboration Examples. • Sharing & Preparing Data– Wordwave segmentations (BBN)– Common broadcast news development sets (LIMSI BBN,CU,SRI)– Shared TDT transcriptions (all sites working on broadcasts)– Shared CTS transcriptions (CU)–
  4. 23 Dec 2004: 50000 most frequent words occurring in 204 million words (MW)of Broadcast News (BN) training data, yielding a vocabulary size of around 55000. ... Again modified Kneser-Ney discountingwas used. The BNLM model was trained on 204MW of Broadcast News data
  5. Speaker Diarisation for Broadcast News

    mi.eng.cam.ac.uk/reports/full_html/tranter_odyssey04.html/
    14 Jun 2004: This paper describes systems developed at CUED and MIT-LL to perform automatic segmentation, clustering and labelling of speakers (and in some cases commercial breaks) in broadcast news data. ... Each data set consists of one 30 minute extract from 6
  6. Cambridge STT Overview P.C. Woodland, H.Y. Chan, G. Evermann, ...

    mi.eng.cam.ac.uk/research/projects/EARS/pubs/woodland_earsfeb04.pdf
    23 Mar 2004: Woodland et al.: Cambridge STT Overview. Outline. • Broadcast News. • Lightly supervised discriminative training. • ... Lightly supervised discriminative training on TDT data. • Improve the English Broadcast News system by adding large amounts of
  7. ADAPTIVE TRAINING USING STRUCTURED TRANSFORMS

    mi.eng.cam.ac.uk/reports/svr-ftp/kai_icassp04st.pdf
    27 May 2004: INTRODUCTION. The majority of state-of-the-art speech recognition systems aretrained on found data, for example broadcast news and telephoneconversations. ... This is consistent with the gains that were obtainedon the Broadcast News task [11].
  8. DEVELOPMENT OF THE 2003 CU-HTK CONVERSATIONAL TELEPHONE…

    mi.eng.cam.ac.uk/reports/svr-ftp/evermann_icassp2004.pdf
    27 May 2004: A word-based 4-gram language model was trained on the acous-tic transcriptions, additional Broadcast News data (427M words oftext) plus 62M words of “conversational texts” collected from theWorld Wide ... Niesler, A.Tuerk, E.W.D. Whittaker and S.J.
  9. ADAPTIVE TRAINING USING STRUCTURED TRANSFORMS K. Yu and M.J.F. ...

    mi.eng.cam.ac.uk/reports/svr-ftp/yu_icassp2004.pdf
    18 Jun 2004: The majority of state-of-the-art speech recognition systems aretrained onfounddata, for example broadcast news and telephoneconversations. ... This is consistent with the gains that were obtainedon the Broadcast News task [11].
  10. Speaker Diarisation for Broadcast News S. E. Tranter† and ...

    mi.eng.cam.ac.uk/reports/svr-ftp/tranter_odyssey04.pdf
    25 Mar 2004: Each data set consists of one 30 minute extract from 6different US broadcast news shows. ... A library of broadcast news shows was made1 using theEnglish TDT-4 training data, excluding the shows from theRT-03s development sets.
  11. Cluster Voting for Speaker Diarisation S.E.…

    mi.eng.cam.ac.uk/reports/svr-ftp/tranter_tr476.pdf
    13 May 2004: 32.2 The Broadcast News Data for Diarisation. 32.3 Diarisation Scoring. 4. ... as convincing on the Broadcast News data, and the system restrictedthe two input segmentations to have the same number of speakers.

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