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9 Aug 2005: We use Isolet1-4 (6240 utterances)to train and speaker-disjoint Isolet5 (1560 utterances) to test. ... The McNemar test finds no significant differences be-tween the Vit or CVit schemes and EM/FL Scheme (at significancelevel. " ).

12 Jan 2005: 10. REFERENCES. [1] NIST, “Benchmark Tests : Rich Transcription (RT),” http://www.nist.gov/speech/tests/rt/. ... ICASSP, March 2005. [19] Linguistic Data Consortium, “Simple Metadata AnnotationSpecification V5,” http://www.nist.gov/speech/tests/rt

15 Feb 2005: General System Architecture. The SMD systems used same generic architecture:TEST DATA.

9 Aug 2005: g g g g g g. decisionthreshold. Figure 7: Test patterns and decision boundary limits for a ‘g–d’ classifier: a) w too small,b) w too large. ... The recurrent connectionthus updates our estimate of the priors, depending on the previous context, y(t 1

9 Aug 2005: As the complexity of the tree increases, the test-set perplexity moves through a global minimum. ... Test-set perplexityUnigram at 36.15 and 36.14 for training- and. test-set respectively.

9 Aug 2005: Figure 3: Annotation Performance on training and test data. The training subset consisted of 1667. ... images, or 90% of the data, with the test subset consisting of the remaining 10%, or 214 images.

9 Aug 2005: In this paper weextend the HME to classification and results are reported for three commonclassification benchmark tests: Exclusive-Or, N-input Parity and Two Spirals. ... The points in the test set are offset vertically from the points in the learning

20 Apr 2005: A validator which uses a classifier to test the regionof the image described by the current state estimate. ... 75 percent thenumber of cycles required by boosting for these. short test sequences (including training the expert).

21 Dec 2005: also see [27]). In AFR tests, such methods are usually outperformed by meth-. ... the data as test input. In all tests, both training data for each person in the gallery,.

9 Aug 2005: cast News Benchmark Test Evaluation, the general procedures used are described and previous. ... Test Evaluation, four sites (BBN, MITRE, SPRACH and SRI) participated and submitted their.

9 Aug 2005: A techniquethat optimises the length of individual n-grams is proposed, and experimental tests show it to lead toimproved results.

15 Jun 2005: The held-out dataset for these experiments wasthe eval03 test set, which consists of 6 hours of data. ... To examine performance on held-out data the eval03 test setwas used.

12 May 2005: been introduced, with NIST reporting re-sults with the Wilcoxon signed rank test for speaker-level averagescore differences. ... Woodland, “SU detection forRT-03F at Cambridge University,” http://www.nist.gov/speech/tests/rt/rt2003/fall/presentations/

9 Aug 2005: Facial features are marked by hand and the al-gorithm is run through these test images, making the nec-essary measurements to define each class space. ... d) Proba-bility = 0.9468. 8. Results. We test the algorithm on 100 256x256 images taken

9 Aug 2005: 62. 6.6 Conclusions. 63. 7 Conclusions 69. 7.1 Acknowledgements. 70. A Significance tests 71. ... A.1 McNemars Test. 71. A.2 Critical ratio for the difference in two s.

9 Aug 2005: An implementation is outlined and demonstrated on test sequences con-taining two motions. ... The first example considerstwo frames from the “foreman” sequence, commonly used to test motion segmentationschemes.

9 Aug 2005: Evaluation is performed over various test sets, typically containing 300 sentences from 10–12new speakers. ... The previous bestresult on this test set was 3.6% reported by CMU.

8 Aug 2005: 0.85. 0.9. 0.95. 1. Test index. Ran. k or. derin. g sc. ... 0.86. 0.88. 0.9. 0.92. 0.94. 0.96. 0.98. 1. Test index. Ran.

9 Aug 2005: The global error covariance matrix foreach network mapping is estimated fromits performance on an unseen test set, andthe Jacobian matrix is found by extendingthe usual error back-propagation formulaeto evaluate the

14 Sep 2005: These cases are discussed in Section 5. Figure 2: Rotation center placement results for four test scenes (un-blurred in top row.). ... Figure 2 shows results the algorithm’s choice of rotation center for a number of differ-ent motions in four test