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20 Feb 2018: Contrasts marked are statisticallysignificant (p < 0.05) using a Kruskal-Wallis rank sum test. ... Test System Num Objective Success Rate Perceived Average WERDialogs Partial Full Success Rate Turns.

20 Feb 2018: The training data con-tains 2207 dialogues and the test set consistsof 1117 dialogues. ... For goals, the gains are always statis-tically significant (paired t-test, p < 0.05).

3 Jul 2018: MGB-3 dev set (5 h). MGB-1 test set (19 h). Results: Aurora4. ... contributed most to the performance gains in our experiments, especially fornoisy test data.

15 Jun 2018: This form of test allows the spoken language pro-ficiency of a non-native speaker of English to be assessed morefully than read aloud tests. ... The BULATS test comprises 5 sections:A. short responses; B. read aloud sentences; C-E.

13 Mar 2018: 418. 2. DATA ACQUISITION SETUP In order to develop the tests here exposed, a set of 3D facial data have been acquired. ... The processing time was shorter than ten seconds even for the worst situation met during test step.

12 Sep 2018: computed over all the test sectionswhere the candidate is required to produce spontaneousspeech. ... xN}, what is the best estimate of thevalue of the function at test point x.

3 Jul 2018: Current results on SUMMA test sets. Language Word Error Rate† (%)English (MGB Challenge) 26.1Arabic (MGB Challenge) 14.7German 34.6Russian 40.0. ... Work is ongoing to transcribe test sets for the remaining languages.

15 Jun 2018: Testing Service (BULATS). The BULATS speaking test has fivesections, all related to business scenarios [19]. ... Test Set Ph/Gr Vit CN. GujaratiPh 34.3 33.7Gr 33.3 32.5. Ph Gr - 31.6.

13 Mar 2018: The model can now be used to classify test imagepatches as text or non-text. ... The test patches were ex-tracted in the same manner as the training patches.

20 Feb 2018: This paper presents the results of the live tests, and compares them with the control test results. ... Some interesting differences between the sys-tems are evident in the live tests.

19 Jan 2018: evaluated by 30 native En-glish speakers using a MUSHRA-like test. ... Eachsubject evaluated 36 different sentences (18male, 18 female). The systems under test were:. •

15 Jun 2018: Data from the Business Language Testing Service(BULATS) English tests was used for training and test. ... To avoid a data mismatch,the recognition hypothesis was used both in training and test.

3 May 2018: Test subjectswere asked to assess the quality of the speech on a 1-5 scale. ... 10 test subjectswere used. Models A and B are compared and models A and C arecompared.

20 Feb 2018: The relevant contextual factors were cho-sen as a result of informal perceptual tests. ... 6. EvaluationA perceptual listening test was conducted to evaluate the com-bined conversions.

15 Jun 2018: The. Table 3:Test audio data summary. Id Set Band Type Dur (hrs). ... Acero, “Estimating speech recogni-tion error rate without acoustic test data,” inEurospeech, 2003.

20 Feb 2018: Adaptatation to a very small amountof sad speech data also resulted in considerably sadder prosody, as confirmed bypreference tests. ... A t-test(p<0.05) on the two samples confirmed that the samples are not statisticallydistinguishable.

13 Mar 2018: This is restrictive in practicein that test data may contain distortions that take it outside the strict ambit of the trainingpositives. ... This can be computed in terms of likelihoods. (1)so then the test becomes (2)where.

20 Feb 2018: Thedata was divided into a test set and a training set (see table 1). ... PPL (held out)WER (test). k sentences. WER. (%) /. PPL. Language Modelling Toolkit [12].

13 Mar 2018: Using the later index,Test-C tests Sequence-I, Test-D tests Sequence-II. The correctratios of the coarse localization are shown in Fig. ... Fig. 9. Layout of the outdoor environment in a campus. Test-E tests Sequence-III.

20 Feb 2018: Objective evaluation. In order to test the performance of the different repair systems,. ... T - O 0.66 0.20 0.14. Table 8: Preference test results.