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20 Dec 2013: The traditional approach to assessing spoken English is to have a well-trained human assessor listen to the test - either live or recorded - and mark the performance on a standardised scale.

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.

13 Jun 2013: Part of theretransmitted data was held-out to form a test set, dev1. ... Foreach of the channels there was 2 to 2.5 hours test data, de-pending on how much of the retransmitting speech passedquality assurance tests.

13 Jun 2013: noisesource (“restaurant noise”), while the 410 test utterances weredistorted by the 6 noise sources with a uniform distribution. ... The first row of table 1 shows the perfor-mance on three test sets.

13 Jun 2013: All the experts (SVMs) of the iSVM share the same C,and the parameter C is tuned on the test set A. ... Figure 5: The performance of the iSVM on test set A with dif-ferent C.

7 Nov 2013: Tandem systems. A language independent acoustic model test on. the target language showed that retraining or adapting of the acous-. ... used for alignments. At recognition time a language specific LM,. trained on the transcriptions from the language

13 Jun 2013: The recognition task is a 5K-word dictationtask with 14 test sets, 330 utterances each. ... In the follow-ing, letters A, B, C, and D will be used to indicate test sets 01,02-07, 08, 09-14, respectively.

13 Jun 2013: This dataset wasfurther split into a training set for the CRF models, and a test setfor evaluation. ... Table 1. Results for the word and grapheme-based KWS systems ontraining and test subsets of dev-1, with no threshold applied to con-fidence scores.

13 Jun 2013: For the test sets, the330 utterance from 8 speakers in the AURORA4 set A were fil-tered by two RIRs, “office1” and “office2”, where the latter wasrecored in another office environment ... Recognition in a noisy andreverberant environment is the

27 Mar 2013: The maximum word accuracy criterion was used to train dis-criminative models on multi-style data using suboptimal alignments.Test set A was used as the validation set to stop training. ... However, in this case the SDM givesimprovement on test set B only.