... word recognitionmodel for ex-tracting nouns. While the previous noun extraction6Actually, about 0.145% of nouns in the test data belong tothese cases.A Syllable Based Word Recognition Model for ... performance.Although the word recognitionmodel is designedto extract nouns in this paper, the model itself ismeaningful and it can be applied to other fields suchas language modeling and automatic ... morphological analy-sis based method (Kim and Seo, 1999; Lee et al.,1999a; An, 1999) and POS tagging based method(Shim et al., 1999; Kwon et al., 1999). The mor-phological analysis based method tries...
... 1].A Taylor model vector is a vector with Taylor model c omponents. When no ambiguity arises, wecall a Taylor model vector simply a Taylor model. Arithmetic operations for Taylor model vectors ... represented by a Taylor model, or• when operations between Taylor models are executed.Example 2.4. Addition of two univariate floating-point Taylor models. For simplicity, we use Taylormodels of order ... naiveTaylor model method is described in Section 4, which is followed by a discussion of Taylor model methodsfor linear ODEs. A nonlinear model problem is used to explain preconditioned Taylor model...
... On Taylor ModelBased Integration of ODEsInterval Arithmetic and Taylor ModelsVerified Integration of ODEsTaylor Model Methods for ODEsVerified Integration of Linear ODEsQuadratic Model ProblemNaive ... Taylor ModelBased Integration of ODEsInterval Arithmetic and Taylor ModelsVerified Integration of ODEsTaylor Model Methods for ODEsVerified Integration of Linear ODEsNaive Taylor Model MethodPreconditioned ... Taylor ModelBased Integration of ODEsInterval Arithmetic and Taylor ModelsVerified Integration of ODEsTaylor Model Methods for ODEsVerified Integration of Linear ODEsNaive Taylor Model MethodPreconditioned...
... PM1/27/2011 1:53:25 PMwww.it-ebooks.infoPREFACE xiii Finally, the book contents are based partially on the undergraduate lectures on model - based visual tracking that I have given at the ... tracking task: models, vision, and tracking. ObjectTrackingPre-processingVisualprocessingDatafusionTrackingTargetUpdateMeasurementDetection/ Recognition TargetPredictionModelsObjectsSensorsEnvironmentFeaturesSamplingOcclusionHandlingDataassociationc01.indd ... LocalprocessingLocalprocessingDetection/ Recognition Detection/ Recognition BayesiantrackingBayesiantrackingtMeastObjtItItShapeAppearanceDegrees offreedomDynamicsSensorsEnvironmentModels−tObj1−tObjΔtΔt+−1tObjPost-processingPost-processingTrack...
... Inc.OO22-35I4/97/J3.OO Facial Expressions in Hollywood's Portrayal of EmotionJames M. Carroll and James A. RussellUniversity of British ColumbiaMuch theory and research on emotion are based on the facialexpressions ... perspective on facialexpressions raisesthe following kinds of unanswered questions:1. What is the natural response of observers to the facial expressions of others? How often do they interpret facial ... analyzed actual facial behavior usedquestionable methods and analyses, but several observationsemerged. Four expressions have been observed in fair numbers,two " ;facial expressions of happiness"...
... PM1/26/2011 3:05:16 PMwww.it-ebooks.infoPREFACE xiii Finally, the book contents are based partially on the undergraduate lectures on model - based visual tracking that I have given at the ... are allowed to “ split ” apart). 2.2.2 Appearance Model Together with geometric attributes, visual tracking may require a model of the surface appearance, specifying the photometric qualities ... modality. 4 . Sampling model features . A predicted target hypothesis, usually the average st−, is used to sample good features for tracking from the unoc-cluded model surfaces. These features...
... of the current morpheme in the trigram language model. The trigram model is smoothed using deleted interpolation with the bigram and unigram models, (Jelinek 1997), as in (1): (1) p(m3 ... would like to thank Martin Franz for discussions on language model building, and his help with the use of ViaVoice language model toolkit. References Beesley, K. 1996. Arabic Finite-State ... F. 1997. Statistical Methods for Speech Recognition. The MIT Press. Luo, X. and Roukos, S. 1996. An Iterative Algorithm to Build Chinese Language Models. Proceedings of ACL-96, pages 139−143....
... i i i ! (DEP model) o (TRI model) "*' rT I I I I I I 200 400 600 800 1000 1200 1400 1600 No. of training sentences Figure 8: Model size Related to the size of model, however, ... Preliminary experiments We have experimented with three language models, tri-gram model (TRI), bi-gram model (BI), and the proposed model (DEP) on a raw corpus extracted from KAIST corpus 3. The ... (1996), we may get much more compact DEP model with very slight increase in entropy. 5 Conclusions In this paper, we presented a language model based on a kind of simple dependency gram-...
... speech recognition system. The language processor consists of a language model and a parser. The language model properly integrates the unification grammar and the Markov language model, while ... based on experimental results. Probabilitv Estimation for Constructed Constituents In order to make the unification -based parsing algorithm also capable of handling the Markov language model, ... summarized. The Laneua~e Model The goal of the language model is to participate in the selection of candidate constituents for a sentence to be identified. The proposed language model is composed...
... CONSTRAINT -BASED EVENT RECOGNITION FOR INFORMATION EXTRACTION Jeremy Crowe* Department of Artificial Intelligence Edinburgh University Edinburgh, EH1 1HN UK j.crowe@ed.ac.uk Abstract Event recognition ... deeper analysis, and so on. Because of this early position in the IE process, an event recognition program is faced with a necessarily shallow textual representation. The purpose of our work is, ... forms of event recognition exist at varying levels of analysis (such as within the abductive reasoning mechanism of SRI's TACITUS system (Hobbs et al., 1991), in a thesaurus -based lexical...