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9 Dec 2006: Rules with probability over a certain threshold are run simultaneously on the test data. ... Rules whose probability exceeds a threshold are then applied to the test data.

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.

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.

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.

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.

22 Nov 2006: Though gains inthe posterior of the correct speaker were obtained in training thesedid not generalise well to the test data. ... Eurospeech, 1997. [11] A. Martin, “The NIST year 2002 speaker recog-nition evaluation plan,” 2002, Available

21 Sep 2006: We used 18randomly selected training/test combinations for reporting identification rates. Comparative Methods. ... 0.9. 1. Dimension. Iden. tific. atio. n ra. te. Effect of the dimension on the test set.

22 Nov 2006: C-Aug ML CML 7.3 9.1. Table 1. Training and test error rates for CAN/CAN’T. ... model (tests on MMI HMMssuggest that this may yield a gain of up to 0.5% absolute).

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.

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,