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29 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].

8 Mar 2000: 9 26 142. Table 1: Training and test material available in broadcast news (min-utes) for music (M) background speaker (BGS), other background(BGO), music and speech (MS), narrow-band (T) ... The test set is split into shows available bothin training and

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.

24 Jul 2003: Development test sets. dev01 40 sides Swbd2 (eval98), 40 sides Swbd1 (eval00), 38 sides Swbd2 cellular(for manual segments). ... CNC P4.[123]P5.[123] 24.1 17.1 20.7%WER on eval03 (current test) for all stages of 2003 system (auto-segments).

25 Mar 2004: http://www.nist.gov/speech/tests/rt/rt2003/spring/docs/ref-cookbook-v2_4.pdf , 17th March 2003. ... 6] NIST, “Benchmark Tests : Rich Transcription (RT),”http://www.nist.gov/speech/tests/rt/. [7] S.E. Tranter, K.

27 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

9 Aug 2005: Vocal tract length nor-malisation (VTLN) was applied in both training and test. ... Similar im-provements have been found on other test sets. 7. FULL VARIANCE TRANSFORMS.

17 Nov 2017: Budapest University of Technology and Economics, Department of Telecommunication and Media Informatics,.

27 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,

9 Aug 2005: They are obtained by optimising the inser-tion penalty and another parameter, the silence probability incre-ment, for each test condition. ... Lynx noisefrom the NOISEX-92 database was added to the test sets at 18dBand 12dB.

9 Aug 2005: where4. is retained inE G. when the test succeeds. In practice the value of is fixed (e.g. ... Training- and test-sets were created by splitting thematerial evenly across these topics in the ratio 95:5, resulting in a vocabulary size of 41097 words.

15 Feb 2005: Presentation Overview. • RT03 Broadcast News System Review• Training & Test Data• Improved Acoustic Model Building. – ... Test set # Shows Size Period. dev03 6 3hrs Jan01eval03 6 3hrs Feb01dev04 6 3hrs Jan01dev04f 6 3hrs Nov03.

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

18 Dec 2003: Multiple training and test sets are used in the experiments in this paper. ... 11. Training only Test onlyBoth dictionaries. single variant. substitutions. insertion. deletionsorA B C.

3 Dec 2008: The ML-SAT test procedure is first run toobtain initial ML speaker transforms. ... There is no need to estimate speaker-specific discriminative transforms on the test data.

17 Jan 2003: Acoustic Training/Test Data. Train on the combined set of 1997 and 1998 data. • ... Development test sets. BNeval98 two 1.5-hour data sets. BNeval02 1-hour data set.

10 Oct 2007: Table 3 shows the P1-P2 perfor-mance3 of these baseline models on the BC and BN tests sets. ... Table 6. Unadapted %CER onbcmdev05. The models were then evaluated on the BC test set,bcmdev05.

15 Feb 2005: Training and Test Data for CTS. The following sets of CTS training data were used:. ... Training and Test Data for BN. The following sets of BN training data were used:.

10 Dec 2003: Training and Test Data Sets. • Acoustic training data. h5train03b 360h data set.– 290h LDC data (SwbI, CHE, Swb Cellular) with MSU/LDC careful. ... Test sets. eval02 5h set from SwbI, Swb2 and Swb Cellular data, 60 conversationseval03 6h set from

29 Apr 2004: There are some small gains using ensemble techniques, but the gains are notconsistent across the dev03f and eval03f test sets. ... The PFM combined with LDCDB98 SULMs can give some small gains, but thepatterns are not consistent across the dev03f and