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  2. Who Really Spoke When? Finding Speaker Turns and Identities in…

    mi.eng.cam.ac.uk/reports/full_html/tranter_icassp06.html/
    9 Dec 2006: Rules with probability over a certain threshold are run simultaneously on the test data. ... Rules whose probability exceeds a threshold are then applied to the test data.
  3. THE CU-HTK MANDARIN BROADCAST NEWS TRANSCRIPTION SYSTEM R. Sinha, ...

    mi.eng.cam.ac.uk/research/projects/AGILE/publications/rs_ICASSP06.pdf
    23 Feb 2006: The finalsystem shows state-of-the-art performance over a range of test sets. ... This approach was not found to perform reliably across differ-ent types of test data.
  4. C:/SFWDoc/Academic/Publications/2006/ICPR_2006/Final_ContGest/icpr_200…

    mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_icpr06a.pdf
    21 Sep 2006: A detailed report of this test can be found in ourprevious work [10]. ... 20.2 fps).Figure 3 illustrates the recognition process on a typical test-ing clip.
  5. WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN ...

    mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp06.pdf
    9 Dec 2006: and probabilitiesFind Ngram rules. human transcriptionand diarisation. (optional)assign categories. test datatraining data. ... Rules whose probability ex-ceeds a threshold are then applied to the test data.
  6. 21 Sep 2006: We used 18randomly selected training/test combinations for reporting identification rates. Comparative Methods. ... 0.9. 1. Dimension. Iden. tific. atio. n ra. te. Effect of the dimension on the test set.
  7. A New Look at Filtering Techniques for Illumination Invariance ...

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_AFG06.pdf
    30 Jan 2006: State-of-the-art commercial system FaceIt by Identix[12] (the best performing software in the most recentFace Recognition Vendor Test [13]),. • ... KLD) [14]. In all tests, both training data for each person in the gallery,as well as test data,
  8. Incremental Learning of Locally OrthogonalSubspaces for Set-based…

    mi.eng.cam.ac.uk/reports/svr-ftp/kim_bmvc06.pdf
    21 Sep 2006: Iden. tific. atio. n ra. te. Effect of the dimension on the test set. ... Anindependent illumination set with both training and test sets was exploited for the val-idation.
  9. C:/SFWDoc/Academic/Publications/2005/BMVC_2005/FinalPaper/bmvc_05_sfwo…

    mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_bmvc05.pdf
    21 Sep 2006: cluttered background, and background with skin colour). The overallaccuracyon 1025 test cases is 89.7%. ... Thepercentage of test cases that cannot be mapped into any classis 20.3%.
  10. WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN ...

    mi.eng.cam.ac.uk/reports/full_html/tranter_icassp06.html/paper.pdf
    9 Dec 2006: and probabilitiesFind Ngram rules. human transcriptionand diarisation. (optional)assign categories. test datatraining data. ... Rules whose probability ex-ceeds a threshold are then applied to the test data.
  11. Face Set Classification using Maximally Probable Mutual Modes Ognjen…

    mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ICPR06.pdf
    29 Apr 2006: To establish baseline performance, we compared ourrecognition algorithm to:. • State-of-the-art commercial system FaceItr by Identix[8] (the best performing software in the recent FaceRecognition Vendor Test [10]),. • ... perform well if imaging

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