Báo cáo khoa học: "A Syllable Based Word Recognition Model for Korean Noun Extraction" potx
Báo cáo khoa học: "A Syllable Based Word Recognition Model for Korean Noun Extraction" potx
... conju-gated forms of verbs. Syllable statistics have beenalso used for automatic word spacing (Shim, 1996;Kang and Woo, 2001; Lee et al., 2002).The syllable based word recognition model is rep-resented ... suitable for the word recognition model. The corpus can be modified through the fol-lowing steps:Step 1 For a given Eojeol, segment word bound-aries and assign word tags to each word. Step 2 For ... A Syllable Based Word Recognition Model for Korean Noun ExtractionDo-Gil Lee and Hae-Chang RimDept. of Computer Science...
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Tài liệu Báo cáo khoa học: "A Discriminative Syntactic Word Order Model for Machine Translation" pdf
... is useful for addressing the search and modelingproblems for MT ordering.4 A Global Order Model for TargetDependency TreesIn the rest of the paper we present our new word or-der model and ... local tree order model outperformed either model by a large margin. This indicates that combin-ing syntactic (from the LTOM model) and surface- based (from the language model) information is veryeffective ... Association for Computational LinguisticsA Discriminative Syntactic Word Order Model for Machine TranslationPi-Chuan Chang∗Computer Science DepartmentStanford UniversityStanford, CA 94305pichuan@stanford.eduKristina...
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Tài liệu Báo cáo khoa học: "A Graph-based Semi-Supervised Learning for Question-Answering" doc
... matching with the S Noun and verb counts in common, separately.–When words don’t match we attempt matchingsynonyms in WordNet for most common senses.–Verb match statistics using WordNet’s cause ... Summarization SSL.of the models. As more labeled data is introduced,Hybrid SVM models’ performance increase dras-tically, even outperforming the state-of-the artMRR performance on TREC04 datasets ... question posed by the user. The ma-jor categories of information extraction producedby our QA system characterizes features for ourTE model based on analysis of q/a pairs. Here wegive brief descriptions...
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Tài liệu Báo cáo khoa học: "A FrameNet-based Semantic Role Labeler for Swedish" pdf
... Lbefore, Ltarget, and Lafter, which correspondto the parts of the list that is before, at, and after the target word, respectively.Initialize chunk-open to FALSE for Lsubin {Lbefore, ... target word. When the target word is a verb, the baseline putsFE brackets around the words included in each ofthese subtrees1. When the target is a noun, we alsobracket the target word token ... roles for all senses of the target word as features for the classifier (as described above).Solving the problem of external ambiguity wasoutside the scope of this work.Some potential target words...
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Báo cáo khoa học: "A TAG-based noisy channel model of speech repairs" pdf
... ob-tained using the bigram model. Because thelanguage model is responsible for generating thewell-formed sentence X, it is reasonable to ex-pect that a language model that can model moreglobal properties ... speech recognition and machinetranslation, and in these applications syntax- based language models P(Y ) yield state-of-the-art performance, so we use one such model here.The channel model ... po-tentially begin before any word of X. When arepair has begun, the channel model incremen-tally processes the succeeding words from thestart of the repair. Before each succeeding word either the...
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Báo cáo khoa học: "A Syntax-based Statistical Translation Model" potx
... .3. For each pair in the training corpus, For all , such that Str ,Let cnt = PStrP For ,+= cnt+= cnt+= cnt4. For each , , and ,5. Repeat steps 2-4 for several iterations.A straightforward ... the model, each nodewas re-labelled with the POS of the node’s head word, and some POS labels were collapsed. For example, labels for different verb endings (suchas VBD for -ed and VBG for ... asdescribed in Section 2.2. IBM Model 5 was se-quentially bootstrapped with Model 1, an HMM Model, and Model 3 (Och and Ney, 2000). Eachpreceding model and the final Model 5 weretrained with five...
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Báo cáo khoa học: "Maximum Entropy Based Phrase Reordering Model for Statistical Machine Translation" docx
... similar andstable performance ranks in different domains andthe MaxEnt -based reordering models achieve thebest performance among them. Using all features for the MaxEnt model (lex + col) is ... entropy based reordering model is em-bedded inside a log-linear phrase -based model oftranslation. Following the Bracketing Transduc-tion Grammar (BTG) (Wu, 1996), we built aCKY-style decoder for ... k-best list is very important for the minimum error rate training (Och, 2003a)which is used for tuning the weights λ for our model. We use a very lazy algorithm for the k-bestlist generation,...
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Báo cáo khoa học: "A Modified Joint Source-Channel Model for Transliteration" ppt
... the need for English pronunciations. The phonetics -based and spelling -based models have been linearly combined into a single transliteration model in (Al-Onaizan and Knight, 2002b) for transliteration ... transformation rules to do back-transliteration. (Stalls and Knight, 1998) adapted this approach for back transliteration from Arabic to English for English names. A spelling -based model ... transliteration problem has been formulated under both noisy-channel model and joint source-channel model in Section 2. A number of transliteration models based on collocation statistics including...
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Báo cáo khoa học: "A Pylonic Decision-Tree Language Model with Optimal Question Selection" potx
... models classify the word histories by their last N - 1 words. N varies from 2 to 4 and the trigram model P{wn [Wn-2, wn-1} is commonly used. Al- though these simple models perform surpris- ingly ... wi denotes the i-th word in the text. Even for a small vocabulary, the space of word histories is so large that any attempt to estimate the conditional probabilities for each distinct history ... probabilities to words following a given text. In contrast with previ- ous decision-tree language model attempts, an algorithm for selecting nearly optimal questions is considered. The model is to...
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Báo cáo khoa học: "A Feature-Rich Constituent Context Model for Grammar Induction" doc
... LLCCM outperforms CCM by13.9% (unlabeled) bracketing F1 and, unlike CCM,outperforms a right-branching baseline on sentenceslonger than 15 words.172 Model The CCM is a generative model for the ... using a log-linear model: Pt(y|x) =exp w, fxytyexpw, fxyt(1)This technique for parameter transformation wasshown to be effective in unsupervised models for part-of-speech ... in-duction, word alignment, and word segmentation(Berg-Kirkpatrick et al., 2010). In our case, replac-ing multinomials via featurized models not only im-proves model accuracy, but also lets the model...
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