Báo cáo khoa học: "Combining Trigram-based and Feature-based Methods for Context-Sensitive Spelling Correction" docx

Báo cáo khoa học: "Exploring Distributional Similarity Based Models for Query Spelling Correction" docx

... designing a spelling correction program for web search queries, however, poses special technical challenges and cannot be well solved by general purpose spelling correction methods. Cucerzan and ... probabilities from corpus (Church and Gale, 1991; Mayes et al, 1991; Ris-tad and Yianilos, 1997; Brill and Moore, 2000; and Ahmad and Kondrak, 2005). In the men-tioned methods, however, the similarities ... 2, we discuss the motivations for our ap-proach, and describe two methods that can make use of distributional similarity information in Section 3. Experiments and results are presented in...

Tài liệu Báo cáo khoa học: "Combining Functionality and Object Orientedness for Natural Language Processing" ppt

... descendants, say z and y, a PAL expression for the phrase is one of the following forms: <z>( <V>) or <p>( <z>) where ~a> stands for a PAL expression for a phrase ~*. ... composite expressions are constructed only with a binary form of function application. Thus, if z and I/ are well-formed formulas of PAL, so is a form z(y). Expressions of PAL are related to expressions ... Combining Functionality and Ob]ec~Orientedness for Natural Language Processing Toyoakl Nishida I and Shuji Doshita Department of Information Science, Kyoto University Sakyo-ku,...

Báo cáo khoa học: "Combining Trigram and Winnow in Thai OCR Error Correction" potx

... areas. Make hypotheses for nonwords and unknown words: (a) For each dubious string obtained from 1., the surrounding words are also con- sidered to form candidates for correc- tion by concatenating ... string. For example, in "in- form at j off', j is an unknown string representing a dubious area, and in- form at and on are words. In this 838 case, the unknown word and its ... adjacent to characters in the upper and lower level, and 2. rarely causes insertion and deletion errors in the middle level. For example, applying the candidate generation routine with 1 edit...

Báo cáo khoa học: "Combining Distributional and Morphological Information for Part of Speech Induction" doc

... DM uses morphological informa-tion as well, DF uses frequency information and DMF uses morphological and frequency informa-tion. We evaluated it for all words, and also for words with frequency ... range from 12.1 for English to4.84 for Hungarian. The tags used are extremelyfine-grained, and incorporate a great deal of infor-mation about case, gender and so on — in Hun-garian for example ... entropy of the gold standard tagsgiven the induced tags. We use the symbol W torefer to the random variable related to the word, G for the associated gold standard tag, and T for thetag produced...

Báo cáo khoa học: "Combining Statistical and Knowledge-based Spoken Language Understanding in Conditional Models" pptx

... leaving no hidden variables and resulting in a CRF. Here, PAC stands for “preamble for arrival city,” and PDC for “preamble for departure city.” The command prior and state transition features ... context and chunk coverage features. The chunk coverage feature has three settings: 0 stands for no chunk coverage features; 1 for chunk coverage features for preamble words only; and 2 for both ... precommands. State 3 and state 6 are called postcommands. States 2, 5, 8 and 9 represent slots. A slot is actually a three-state sequence — the slot state is preceded by a preamble state and...

Báo cáo khoa học: "Combining Acoustic and Pragmatic Features to Predict Recognition Performance in Spoken Dialogue Systems" pdf

... GUI.The DMT and AT are the core components of In-formation States. The SL and MB are subsidiarydata-structures needed for interpreting and generat-ing anaphoric expressions and deﬁnite NPs. ... of Informa-tion States (IS) and the update procedures for pro-cessing user input and generating system responses.Here, we brieﬂy introduce parts of the IS which areneeded to understand the ... vectors for automatic classiﬁca-tion. The feature vectors combine recognizer con-ﬁdence scores, low-level acoustic information, in-formation from WITAS system Information States, and domain...

Báo cáo khoa học: "Combining Stochastic and Rule-Based Methods for Disambiguation in Agglutinative Languages" pptx

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Báo cáo khoa học: "Combining data and mathematical models of language change" ppt

... the V forms of {1,1} pairs to be mis-perceived as σ´σ, and for the N forms of {2,2} pairsto be misperceived as ´σσ.3 Modeling preliminariesWe ﬁrst describe assumptions and notation for models ... both — is possible for someparameter values. (0, 0) and (1, 1) (correspondingto {1,1} and {2,2}) are technically never possible,but effectively occur for FPs of the form (κ, 0) and (γ, 1) when ... Harada, and R.P. Wayland.2003. Factors affecting stress placement for Englishnonwords include syllabic structure, lexical class, and stress patterns of phonologically similar words.Language and...

Báo cáo khoa học: "Combining Deep and Shallow Approaches in Parsing German" pptx

... dependent in left-to-right or-der (e.g. 0 for in, 1 for onin example (5)), and anumber designating the head in left-to-right (e.g.0 for saw, 1 for man, 2 for hillin (5)). If the linksare stored ... representations,Riezler et al. (2002) distinguish upper and lowerbound, standing for optimal performance in disam-biguation and average performance, respectively. InI-tags T-tagsF-val prec rec ... syntactic3grammaticalroles. We added three roles for marker comple-ments (CMP), speciﬁers (SPR), and ﬂoating quanti-ﬁers (NK+), and subtracted the roles for conjunctionmarkers (CP) and coreference with expletive...

Báo cáo khoa học: "Combining Linguistic and Gaze Features to Resolve Second-Person References in Dialogue" docx

... GDP as thecandidate. Hence, we compute a candidate target for the utterance overall, for each third of the ut-terance, and for the period -/+ 2 seconds from the276you start time, and in addition, ... http://corpus.amiproject.org/documentations/guidelines-1/275 For each participant Pi– target for whole utterance– target for ﬁrst third of utterance– target for second third of utterance– target for third third of utterance– target for -/+ ... Christoudias2,Trevor Darrell2 and Stanley Peters11Center for the Study of Language and Information, Stanford University{frampton, raquelfr, ehlen, peters}@stanford.edu2International Computer...

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