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16 Feb 2008: 120,000 instances in the training set. 8,000 instances in the test set. ... Lattice-based MMIE was performed. Test:. Test set is 8400 utterances ( 25 hours) from 10 heldout speakers.

20 Feb 2018: 2013). In making com-parisons it should be noted that this team did notalter the training for different test sets, and submit-ted only one entry. ... Williams, Kai Yu,Steve Young, and Maxine Eskenazi. 2011. Spokendialog challenge 2010: Comparison of live

12 May 2016: Business Language Testing Service (BULATS) Spoken Tests. • Example of a test of communication skills A. ... Statistical Parser Features. • Parser features from RASP system improve grades for written tests. •

9 Aug 2005: The test-set wassubjected to the same preprocessing steps as the training corpus. ... The OOV rate for the describedvocabulary is 0.62% on the test-set.

19 Sep 2003: Fig. 1. Test set word error rate for all possible models, with thestandard front-end 12, 16 and 24 component performance. ... there was some random variation in the performance,since we do not have an infinite held out test set.

8 Mar 2000: approach, and two sets of HMMs were adapted.The test data for F2 was also automatically labelled as narrow. ... 1995 Hub-4 “Dry-Run” Broadcast Materials Bench-mark Tests. Proc. DARPA Speech Recognition Workshop, Har-riman, New York.

12 May 2005: been introduced, with NIST reporting re-sults with the Wilcoxon signed rank test for speaker-level averagescore differences. ... Woodland, “SU detection forRT-03F at Cambridge University,” http://www.nist.gov/speech/tests/rt/rt2003/fall/presentations/

22 Jul 2021: In addition, therecording conditions and levels of background noise can vary con-siderably across countries and test centres. ... Scores for each sec-tion of the test were generated by trained graders, operating withinlocal test centers.

25 May 2004: κ is a scalingfactor and can be adjusted to improve test-set performance. ... Table 3. Comparison of WER for MPE trained HLDA and EM-LLT models on thedev01sub test set.

20 Feb 2018: Statisticalsignificance was computed using a two-tailedStudent’s t-test, between deep and all others. ... Statistical significance was computed usingtwo-tailed binomial test. Pref.% classlm rnn w/ sc-lstm deep.

14 Sep 2010: In addition to background additive noise convolutional distortion wasadded to test set C. ... Table 3VTS (γ = 1) and SVM rescoring performance WER (%) tests sets A, B, C (ϵ = 2)using HTK features, SVMs trained on test set A N2-N4 10-20dB SNR.

20 Feb 2018: In the evaluation, the training corpus is used to train a semanticdecoder, then the whole test corpus is decoded. ... The F-score, ICE anddialogue act type accuracy for each test utterance are then calculatedand averaged.

6 Jun 2014: A query is a textual phrase containingone or several terms. We focus in the NTAR (no test audio re-use) task where the system components and word indices arefrozen before the ... The training datais basically telephone conversational data and some

20 Feb 2018: This could be dueto the relatively short horizon in the test-bed problem, as most of the dialogues. ... Three handcrafted policies were created for the test-bed dialogue manage-ment problem, called HC1, HC2, and HC3.

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.

22 Jun 2007: For theBN test set, cross-adaptation in either direction gave gains of about0.5% absolute over the best individual system. ... The first half of this test set was used for tuning the translation.

27 May 2004: GI unadapted single pass decoding system. Table 2 gives WER on the test sets using the5xRT P1-P2system. ... thedev03 and eval03 test sets respectively.These results were even slightly better than the full 10xRT CU-.

2 Mar 2009: increased adaptation power on unseen test data can compensatefor this and achieve overall improvements. ... Statistical significance tests showed that almostall additional gains with different MLLR improvements weresignificant13.

1 Mar 2023: Test set dialogues aregrounded in 6 schemas seen during training and 15unseen ones. ... 6It appears in 4 unseen services in the test set.7Lee et al.

31 May 2001: Acoustic Training/Test Data. h5train00 248 hours Switchboard (Swbd1), 17 hours CallHome English (CHE). ... Training on simulated GSM coded data helps when test uses same process butnot real cellular data! •

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,

9 Aug 2005: The calculation of perplexity is based on the probability thatthe language model assigns to some test text. ... Thus perplexity is based solely on the probabilities ofthe words which actually occur in the test text.

22 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.

20 Feb 2018: For example, before we replace theslot “departure.day” by “arrival.day”, we should test whetherthe word “arrive” is near the slot’s lexical realisation. ... He& Young detail the test data extraction process in [8]. Our second dataset

10 Dec 2003: Adaptive Training with Structured Transforms. Initial Results on 16-Component System. System Training Test EstimationAdaptation Adaptation MLE MPE. ... Adaptive Training with Structured Transforms. Initial Results on 28-Component System. System Training

1 Apr 2005: Furthermore, we excludedtdt4 data after 15 Jan-uary 2001 so not to have temporal overlap of acoustic or languagemodel data with the development test sets. ... The resultsstill showed consistent gains over various test sets. Finally we usedthe

25 Sep 2003: Table 1. The WER(%) on test set CEDFÑ _ for MMI/MPE systemsand discriminative SAT systems, after constrained MLLRadaptation. ... Furthermore, the useof MMI-based constrained DLT for building an MPE-SAT modelcould also get similar test-set performance.

3 Apr 2014: The trainingset consisted of 175 speakers while each test set contained 8 speak-ers. ... We split the corpusinto training and test sets in the same way as in the SDM task.

20 Feb 2018: The first part compares simulated user re-sponses to real user responses in an unseen test set. ... Also as expected, the training data performanceis slightly better than the test data performance.

9 Aug 2005: Training- and test-sets werecreated by splitting the material evenly acro ss these topics in the. ... A 65K vocabulary was used to build language models. Thestandard 2.1 million word set-aside dev-test text for WSJ0 was used as a test-set.

20 Feb 2018: Finally, recognition experiments onthe test set of this task show that the proposed model givesan improvement over a standard HMM with a comparablenumber of parameters. ... This task consists of 72 hours of training data and 3hours of test data.

22 Mar 2017: If thenormalisation termZ(hi) could be approximated as constantC, un-normalised RNNLM probabilities are be used in test time as,. ... In test time, RNNLM probabilities canbe approximated as unnormalised probabilities in Eqn (3) and fastevaluation speed

20 Feb 2018: required realisations are already well represented in the trainingdata. This was also observed in the listening test presented inthe following section. ... The number of judgements per comparison as well asthe statistical significance level estimated

16 Mar 2005: Further details andan implementation of the K-S test can be found in [27]. ... 10. 20. 30. 40. 50threshold for KS test statistics. threshold for KS test statistics.

10 Jan 2005: nist.gov/speech/tests/rt/rt2003/spring/docs/rt03-spring-eval-plan-v4.pdf , 25th February 2003. ... 3] NIST, “Fall 2004 Rich Transcription (RT-04F) EvaluationPlan,” http://www.nist.gov/speech/tests/rt/rt2004/fall/docs/rt04f-eval-plan-v14.pdf , 30th

22 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

20 Feb 2018: Experimental results. A subjective listening test was performed to measure the abil-ity to convey emphasis. ... It can be observed that all contextadaptive training systems obtained better emphasis detectionperformance than the standard full

20 Feb 2018: utterances and the 2 reference paraphrasesover a test corpus (with n up to 4). ... Each utterance is taken from the test folds ofthe cross-validation experiment presented in Sec-tion 5.2, i.e.

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%.

9 Aug 2005: citation words, number sequences and prose passageswere used, with one quarter of the data ( 1500 phonemes) setaside as a test set. ... 6. RESULTSResults for both phoneme and word recognition over 50 test utter-ances with.

5 Oct 2000: While MMIE is very effective at reducing training set error a keyissue is generalisation to test data. ... On other test setsimprovements greater than 1% absolute have also been obtained and.

6 May 2008: NIST 2008 Arabic-English MT evaluation development 8. Lowercase BLEU scores over three test sets from 2002 through 2006:. ... 8 nist.gov/speech/tests/mt/2006 nist.gov/speech/tests/mt/2008Department of EngineeringUniversity of Cambridge. NIST Open Machine

28 Apr 2005: increasing mixtures.• Obtain prob from each SU subtype GMM for each feature vector in test data.• Place GMM probs on arcs of lattice and decode as usual. ... Initial GMM results for dev03f test set:. SYSTEM DEL INS SUBS %Err.

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.

28 Apr 2014: The results are listed in Table 1. On test set A and B,the iSSVM get around 3% relative improvement in all SNRs,but quite small improvement is achieved on test ... The parameter C is tunedon the test set A illustrated in Fig 2.

20 Feb 2018: In order to validate and test a semantic decoder for compliance with the above specification,a standard semantic decoder called SemDecode and two Perl scripts are supplied:. ... SemScore.pl semtst semref. This script reads a test semantic map file and a

20 Feb 2018: Table 3: Pairwise comparison between four systems. Two quality evaluations (rating out of 5) and onepreference test were performed in each case. ... Statistical significance was computed using a two-tailedWilcoxon rank sum test and a two-tailed binomial

25 Feb 2019: able to derive practical confidenceestimates mitigating the problem of sacrificing either com-putational complexity or test accuracy. ... NLL) on the test set when compared to the FA model (89.952vs.

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 Aug 2005: British Machine Vision Conference 4. Figure 2: A selection of the test images. ... test and Jef-frey divergence (identical) (C&J), and the EarthMover distance (EM).