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Generating and Evaluating Segmentations for Automatic Speech…
mi.eng.cam.ac.uk/reports/full_html/tranter_icassp04.html/13 Jul 2004: NIST,. Benchmark Tests : Rich Transcription (RT). -
EARS STT Overview Phil Woodland February 4th 2004 Cambridge ...
mi.eng.cam.ac.uk/research/projects/EARS/pubs/woodland_board_earsfeb04.pdf23 Mar 2004: Woodland: STT Overview. Measuring STT Progress. Current Test Sets : Traditional NIST speech recognition evaluation approach. • ... Progress Test Set : Fixed test set to eliminate test-set variability for trackingprogress towards program goals. • -
Speaker Diarisation for Broadcast News
mi.eng.cam.ac.uk/reports/full_html/tranter_odyssey04.html/14 Jun 2004: This was to simulate conditions in the RT-03s evaluation, where there was a temporal gap between the test-audio and the training shows. ... To help minimise the cost of computing the BIC statistics at every point, a faster Hotelling's T test is first -
Experiments with Fisher Data Gunnar Evermann, Bin Jia, Kai ...
mi.eng.cam.ac.uk/research/projects/EARS/pubs/evermann_sttmay04.pdf25 May 2004: Test setseval03 6h set from Fisher and Swb2-5 data, 72 conversationsdev04 3h set from Fisher, 36 conversations. ... WER on eval03, fsh2004sub models, unadapted, 2003 trigram. Test with adaptation in P1-P2 system:. -
ADAPTIVE TRAINING USING STRUCTURED TRANSFORMS
mi.eng.cam.ac.uk/reports/svr-ftp/kai_icassp04st.pdf27 May 2004: During training and test adaptation, a global in-terpolation weight was estimated and separate speech and silencetransforms were used for CMLLR. ... Using ST for test adaptation again yieldedabout the same as a GD system with CMLLR. -
Diarisation Research at CUED Sue Tranter and Srinivasan Umesh ...
mi.eng.cam.ac.uk/research/projects/EARS/pubs/tranter_mdetechmay04.pdf29 Apr 2004: Test on different systems, architectures and data sets. • Allow more than 2 inputs. ... Use dual-phone recogniser to remove long silences. • Use LIMSI-style segmentation/clustering algorithm [ NB - parameters havebeen chosen on the test data]. -
ADAPTIVE TRAINING USING STRUCTURED TRANSFORMS K. Yu and M.J.F. ...
mi.eng.cam.ac.uk/reports/svr-ftp/yu_icassp2004.pdf18 Jun 2004: During training and test adaptation, aglobal interpolation weight was estimated and separate speech andsilence transforms were used for CMLLR. ... Using ST for test adaptation again yieldedabout the same as a GD system with CMLLR. -
Precision Matrix Modelling for LVCSR K.C. Sim & M.J.F. ...
mi.eng.cam.ac.uk/research/projects/EARS/pubs/sim_sttmay04.pdf27 May 2004: Experimental Setup• Unadapted results• Conversational telephone speech – English (CTS):. – Training dataset: h5etrain03 (296hr)– Test dataset: dev01sub (3hr) & eval03 (6hr)– CMN, CVN and VTLN are used– Basis vectors/matrices: ML trained -
GENERATING AND EVALUATING SEGMENTATIONS FOR AUTOMATIC…
mi.eng.cam.ac.uk/reports/svr-ftp/tranter_icassp04.pdf25 May 2004: 8. REFERENCES. [1] NIST, “The Rich Transcription Spring 2003 (RT-03S)Evaluation Plan, version 4,” http://www.nist.gov/speech/tests/rt/rt2003/spring/docs/rt03-spring-eval-plan-v4.pdf , ... 2] NIST, “Benchmark Tests : Rich Transcription (RT),”http:/ -
Ongoing Experiments with Lightly SupervisedDiscriminative Training…
mi.eng.cam.ac.uk/research/projects/EARS/pubs/chan_sttmay04.pdf27 May 2004: Training and Test Data Sets. • Acoustic training dataTDT4 Oct 2000 - Jan 2001. – ... Corrected closed-captions subset– 370 shows, 250h recorded broadcasts. • Test setsdev03 17th Jan 2001 - 31 Jan 2001 (6 shows, 3h data)eval03 Feb 2001 (6 shows,
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