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8 Aug 2005: 4. Includ ing EdgeOrientation Impr ovesClassificationPerformance.Thisexampleshowsthe classificationresultson a test setusing a marginalized template.

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.

9 Aug 2005: The word error rate resultsare based on the six shows of the 1996 Hub 4 development test,and were generated by rescoring lattices produced by a simplifiedversion of the 1996 Hub

12 Jul 2005: Foreach individual in the database we collected a training and a test video sequenceof the person’s face in random motion, sampled at 10fps. ... Illumination conditions were mildly different in training and test sequences,see Figures 8 and 9.

10 Jul 2005: Training of allalgorithms was performed with data acquired in a single illumination setting and testingwith a single other – we used 9 randomly selected training/test combinations. ... time 7.8 11.8 11.8 0.8 45 7.0 7.0. Table 2:Evaluation results:The

26 Sep 2005: to test it. This was recognised early on, thus most noise robustness methods can be classified under several. ... Test Conditions. Figure 3.1: Methods of reducing the acoustic mismatch. 3.1 Inherently Robust Front-Ends.

9 Aug 2005: A good approximate loglikelihood score was found empirically. To test whether the GS performance degrades below the 1.6 tailthreshold due to the state likelihoods of components within a se-lected

9 Aug 2005: Section 5. evaluates methods using the SQALEUS-English test set and Section 6.

9 Aug 2005: c) aspectratio = 1:1 (201 points). We do a further test by varying the aspect ratio of thepreattentive filter.

8 Aug 2005: Thisis the underlying principle of the Likelihood Ratio Test (LRT). It could be easily shownthat using likelihood ratios minimizes the Bayesian error in two-class decision problems[20].

9 Aug 2005: hood estimate, then an OpenGL implementation is possible.The model is repeatedly rendered using the 0 -test, with anincreasing probability threshold.

8 Aug 2005: We performed 25 recognition tests, using each database for training and testing it against all the others.For each person in a database we collected a data set consisting of

9 Aug 2005: cd/opal/timit/test/dr4/mbns0/sx320 ). Ampl. itude. h#dhaxn ih r ixs ih nxix gclgaa gclm ey n aa pclbiy w axth ix n w ao kclk ix ng

9 Aug 2005: Test-set perplexity. Training-set perplexity. Test-set, count thresholdprune. 1e-4. 5e-5. 2.5e-5. 1e-5.

9 Aug 2005: We carried out three additional experiments to test the gen-erality and robustness of our approach:.

9 Aug 2005: The fronto-parallel view reveals how the inter-section tests can be performed efficiently.

28 Jul 2005: As a test,EPZS was applied to synthetic data of the same form as used in Figure 4, where much higherstrains were simulated.

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9 Aug 2005: high-noise test speechunknown utterance from. high-noise speech. 10 hmms modelling. adjusted set of. ... each state known. cepstral means in. mse. normalised. accumulate. digit-dependentdigit-dependent. noisy test.