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27 Jul 2020: Abstract for niesler_tr265. Cambridge University Engineering Department Technical Report CUED/F-INFENG/TR265. COMPARATIVE EVALUATION OF WORD- AND CATEGORY-BASED LANGUAGE MODELS. Thomas Niesler and Phil Woodland. July 1996. Conventional n-gram

27 Jul 2020: Results are presented for the 2001 development test set and the 2002 evaluation set.

27 Jul 2020: The results show that the proposed method is very much faster yet performs acceptably compared to conventional systems which depend on keyword-specific training or prior knowledge of the test set

27 Jul 2020: Because the compensation is word-dependent, its application needs to be hypothesis-driven on the test material.

27 Jul 2020: An implementation is outlined and demonstrated on test sequences containing two motions.

27 Jul 2020: The paper also presents results on a new set of 60 queries with assessments for the TREC-6 test document data used for development purposes, and analyses the relationship between recognition

21 Feb 2022: Business Language Testing Service (BULATS) Spoken Tests. • Example of a test of communication skills A. ... NICT Japanese Learner English (JLE) • Manual transcription of interviews from English oral proficiency test. •

2 Mar 2009: 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.

20 Feb 2018: 1 Introduction. Speaking tests for assessing non-native speakersof English (NNSE) often include tasks involvinginteractive dialogue between a human examinerand a candidate. ... Williams, Kai Yu, Steve Young,and Maxine Eskenazi. 2011. Spoken dialog

2 Mar 2009: To further refine the LM, unsupervised test-setadaptation to a particular broadcast show, for example, may beused. ... 5. ConclusionUnsupervised test-time context dependent adaptation of n-grammixture models using a discriminative method was

22 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.

10 May 2000: The TREC-8 SDR test collection[1] usedfor the experiments consists of 21,754 spoken documentsand 49 written queries. ... expansion. Thisparallel collection was larger and thought to be more re-liable than the automatically transcribed test collection.

20 Feb 2018: There were in total47 distinct semantic slots. To parse a test sentence, it was first preprocessed to apply thesame lexical class substitution as used in training, then aligned toeach of the ... 4.2. Results. The Y-clustering approach was tested using

20 Feb 2018: During the control tests, each site taking partin the challenge was asked to find test volunteers. ... Table 2. Overall performance for the Lets Go! spoken dia-logue challenge control tests.

22 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.

30 Sep 2019: NICT-JLE: oral proficiency test interviews. • CLC: range of written exams at different grade levels. ... 10. Boosting GED Performance on Spoken BULATS. 11. • Fine-tune CLC system with 80% data, dev 10%, test 10% x10. •

20 Dec 2011: Phonetic Pronunciations for Arabic Speech-to-Test Systems. ICASSP 2008. C. Longworth and M.J.F.

21 Feb 2022: Automate (English) spoken language assessment & learning• without simplifying/limiting form of test: “free speaking”• possibility for richer, interactive, tests• desire to assess communication skills. ... 5/56. Spoken Language Assessment &

20 Feb 2018: The aim of this test was to formally evaluate the reduction of breathiness observed in TE speech following glottal source replacement. ... All subjects were naïve raters, unfamiliar with TE speech. Results of the pair-wise perceptual tests are

20 Feb 2018: Altogether 21 listeners, 11 native and 10 non-native,participated in the listening test. ... Statistical significance tests were performed assuming a bino-mial distribution of each choice.

10 Jan 2005: gram. The reduction is greater if PLSA’straining text relates to the test set. ... The test set perplexities were calculated on the re-maining half of eval03 (eval03tst).

20 Feb 2018: Reducingthenumber of system components leads to a simpler architecturethat iseasier to implement and test. ... Table 4. Analysis of detected speech segments using V2 and A2models on noisy test setGM2b.

20 Feb 2018: 1. English STC baseline tested on the English test set asreported in [6]. ... Table 2: BLEU scores [?] over the test set translated usingGoogle Translate and Moses.

20 Feb 2018: The set of possi-ble values for each slot was different in the test set, which alsoincluded extra slots. ... A summary of the difference between thesmaller training domain and extended test domain of DSTC3is given in table 1.

19 Apr 2000: The windows were compared to a library of windows stored from previous shows from the broadcaster (the broadcast history) [In theory all the data in the test collection could be used ... The amount of commercial rejection with the VOA data is low, due

19 Jun 2023: Feedback 140. Speech Processing. 21. Free speaking prompt-response tests – speak for up to 1 minute. ... INTERSPEECH 2020. • S. McKnight et al, “Automatic Assessment of Conversational Speaking Tests”, UK Speech C.

20 Feb 2018: Section 4 presents the results of bothobjective and subjective tests. Conclusions then follow. ... 4.2. Subjective listening tests. The previous objective measures show useful comparison infor-mation.

22 Jun 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.

24 Jul 2003: Backchannels not labelled separately in the training data.• Only the test data has reference ctm/mdtm files. - ... Bigram SULMs give largest reductions in %Err when combined with the PFM(using the current training and test data!). •

20 Feb 2018: Two tailed z-tests at the 95% confidence levelwere used to test the statistical significance of the differencebetween the success rates. ... The use of the AMT workers is substantially more efficientwhen compared to a controlled test.

13 Jun 2013: As the test data was Levantine Arabic,there is little appropriate data for training language models. ... Forthis work all the clean Levantine Arabic transcriptions, exclud-ing the dev1 test data, was used.

16 Jun 2008: During recognition the following procedure is used:1. Compensate the acoustic models for the test noise con-. ... dition2. Recognise the test utterance Y to obtain 1-best hypoth-. esis, h = h1,. ,

14 Sep 2010: All three test sets, A, B and C,were used for evaluating the schemes. ... This work used three of the test sets containing digit. sequences (phone numbers).

15 Aug 2007: Thispaper shows that multistyle models benefit from VTS compensationor Joint uncertainty decoding by reducing the mismatch betweentraining and test. ... Figures are reported against thedev03 test set encompassing3 hours of shows from six different news

23 Jun 2003: Acoustic Training Set-Up. • Acoustic/Training Test Data:– training data: 34.9 hours, 379 sides, from LDC CallHome (22.4hrs) and. ... dev02 numbers use manual segmentation, eval03 uses automaticsegmentation. • Comparison of dev02 and eval03

20 Feb 2018: test set. Although this biased the NOV93 results, later analysis showed that the. ... DEC94 test sets. The resulting noisy speech utterances had signal-to-noise ratios.

27 Sep 2000: VTLN warping in training and test both for GI and GDmodels for full and reduced bandwidth coding. ... 8. ACKNOWLEDGEMENTS. We would like to thank BBN for providing the MiniTrain trainingand MTtest test set definitions.

20 Feb 2018: The training data had 276K words in 23K sentences while both the developmental set and the test set consisted of 10K words in 1K sentences. ... All sentences that contained out-of-vocabulary words were removed from the test set.

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.

20 Feb 2018: natural example from each wave file pair. Altogether 16 listeners, 8native and 8 non-native, participated in the listening test. ... The resultis shown in Fig. 4. Statistical significance tests were performed assuming a bino-mial distribution of each

21 Feb 2022: Automate (English) spoken language assessment & learning• without simplifying/limiting form of test: “free speaking”• possibility for richer, interactive, tests• desire to assess communication skills. ... 4/45. Spoken Language Assessment &

19 Nov 2010: The two forms of modified tail distribution modelling were inves-tigated on the 1998 Hub4 partitioned evaluation test set. ... The test was performed on a subset of the 1997 par-titioned evaluation that was used for development [4].

8 Mar 2000: Figure 3: Network prediction on training and test data. Actual output[.

20 Feb 2018: He & Youngdetail the test data extraction process in [3]. Since the ATIS databaseis relatively large, all categories are treated as non-enumerable.1. ... over results reportedby He & Young using the HVS model on the same test set [4], but1.4% lower

20 Feb 2018: It is also important that theparticipants do not interact before the test is started. ... The con-fusion matrix can be trained on phone-labelled test output datafrom an ASR system.

10 Jan 2005: NIST,. Benchmark Tests : Rich Transcription (RT),.

20 Feb 2018: The aim of the experiment was to test the robustness and performance of a spoken dialogue system in a moving car. ... The resulting speech database was further split into a training set (60%) and a test set (40%).

12 Apr 2005: For MLLR mean adaptation, a. SystemAdapt Test Set WER (%)Config eval03 dev04 dev04f. ... This system wasevaluated on botheval03 and dev04 test sets and comparedwith the SATDIAGC system.

16 Sep 2003: Procedure. Training only Test onlyBoth dictionaries. single variant. substitutions. insertion. deletionsorA B C. ... Pronunciation variants in training and test. Combining different strategies in training and test.

8 Sep 2010: Test set A was used as the development set for tuningparameters for all systems, such as the penalty factor Cfor SVMs. ... The integratedtraining yielded a 9% reduction in error rate. The full results for all three test sets are shown in TableII.