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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. -
DEVELOPMENT OF THE CUHTK 2004 MANDARIN CONVERSATIONAL TELEPHONESPEECH …
mi.eng.cam.ac.uk/~mjfg/gales_ICASSP05.pdf22 Nov 2006: The final un-adapted performance on the dev04PE test set was 41.6%. ... Table 5 shows the effect of theuse of an automatic segmenter on the dev04 test data. -
THE CU-HTK MANDARIN BROADCAST NEWS TRANSCRIPTION SYSTEM R. Sinha, ...
mi.eng.cam.ac.uk/~mjfg/sinha_ICASSP06.pdf22 Nov 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. -
C:/SFWDoc/Academic/Publications/2006/ICPR_2006/Final_ContGest/icpr_200…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_icpr06a.pdf21 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. -
WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN ...
mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp06.pdf9 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. -
Discriminative Adaptation for Speaker Verification C. Longworth and…
mi.eng.cam.ac.uk/~mjfg/longworth_INTER06.pdf22 Nov 2006: Though gains inthe posterior of the correct speaker were obtained in training thesedid not generalise well to the test data. ... Eurospeech, 1997. [11] A. Martin, “The NIST year 2002 speaker recog-nition evaluation plan,” 2002, Available -
Learning Discriminative Canonical Correlationsfor Object Recognition…
mi.eng.cam.ac.uk/reports/svr-ftp/kim_eccv06.pdf21 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. -
AUGMENTED STATISTICAL MODELS FOR SPEECH RECOGNITION M.I. Layton and…
mi.eng.cam.ac.uk/~mjfg/layton_ICASSP06.pdf22 Nov 2006: C-Aug ML CML 7.3 9.1. Table 1. Training and test error rates for CAN/CAN’T. ... model (tests on MMI HMMssuggest that this may yield a gain of up to 0.5% absolute). -
A New Look at Filtering Techniques for Illumination Invariance ...
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_AFG06.pdf30 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, -
Incremental Learning of Locally OrthogonalSubspaces for Set-based…
mi.eng.cam.ac.uk/reports/svr-ftp/kim_bmvc06.pdf21 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. -
THE CU-HTK MANDARIN BROADCAST NEWS TRANSCRIPTION SYSTEM R. Sinha, ...
mi.eng.cam.ac.uk/research/projects/AGILE/publications/rs_ICASSP06.pdf23 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. -
C:/SFWDoc/Academic/Publications/2005/BMVC_2005/FinalPaper/bmvc_05_sfwo…
mi.eng.cam.ac.uk/reports/svr-ftp/sfwong_bmvc05.pdf21 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%. -
WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN ...
mi.eng.cam.ac.uk/reports/full_html/tranter_icassp06.html/paper.pdf9 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. -
IEEE TRANS. ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2007 ...
mi.eng.cam.ac.uk/~mjfg/gales_ASL.pdf22 Nov 2006: The various models andrecognition configurations are evaluated using several recent BNdevelopment and evaluation test sets. ... Test set # Shows Hours Period. dev03 6 3 Jan. 2001eval03 6 3 Feb. -
JOURNAL OF IEEE TRANS. ACOUST., SPEECH, SIGNAL PROCESSING, JULY ...
mi.eng.cam.ac.uk/~mjfg/sim_SAP06.pdf22 Nov 2006: Only 0.3% improvement wasobtained on this test set. 3See http://htk.eng.cam.ac.uk/docs/cuhtk.shtml4Significance tests were carried out using the NIST Scoring Toolkit. ... These systems wereevaluated on thedev03 andeval03 test sets, each consistingof 3 -
Augmented Statistical Models for SpeechRecognition Mark Gales &…
mi.eng.cam.ac.uk/~mjfg/Edin_talk.pdf5 Jul 2006: Evaluation on held-out data (eval03)– 6 hours of test data– decoded using LVCSR trigram language model– baseline using confusion network decoding. ... φcn(O; λ) =[ F(ω1) F(ω2). φ(O; λ). ]. • Incorporating in score-space requires consistency -
Face Set Classification using Maximally Probable Mutual Modes Ognjen…
mi.eng.cam.ac.uk/reports/svr-ftp/arandjelovic_ICPR06.pdf29 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 -
TextonBoost: Joint Appearance, Shape andContext Modeling for…
mi.eng.cam.ac.uk/reports/svr-ftp/shotton_eccv06.pdf15 Feb 2006: e) A test input with textons t1 and t2 in the same relative positionas that of training. ... Quantitative evaluation. Figure 8 shows the confusion matrix obtained byapplying our algorithm to the test image set. -
INCREMENTAL BAYESIAN ADAPTATION K. Yu and M.J.F. Gales Engineering ...
mi.eng.cam.ac.uk/~mjfg/yu_ICASSP06.pdf22 Nov 2006: 3. INCREMENTAL BAYESIAN ADAPTATION. The Bayesian adaptation discussed in section 2 runs in a batchmode where all test data are assumed to be available before adap-tation. ... Theperformance was evaluated on the 2003 evaluation test dataset,eval03, -
Modelling Dependencies in SequenceClassification: Augmented…
mi.eng.cam.ac.uk/~mjfg/gales_UEA06.pdf22 Nov 2006: Evaluation on held-out data (eval03)– 6 hours of test data– decoded using LVCSR trigram language model– baseline using confusion network decoding. ... φcn(O; λ) =[ F(ω1) F(ω2). φ(O; λ). ]. • Incorporating in score-space requires consistency
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