Xem 1-20 trên 9517 kết quả Models of english
  • In this paper we discuss our approach toward establishing a model of the acquisition of English grammatical structures by users of our English language tutoring system, which has been designed for deaf users of American Sign Language. We explore the correlation between a corpus of error-tagged texts and their holistic proficiency scores assigned by experts in order to draw initial conclusions about what language errors typically occur at different levels of proficiency in this population.

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  • We present a statistical model of Japanese unknown words consisting of a set of length and spelling models classified by the character types that constitute a word. The point is quite simple: different character sets should be treated differently and the changes between character types are very important because Japanese script has both ideograms like Chinese (kanji) and phonograms like English (katakana). Both word segmentation accuracy and part of speech tagging accuracy are improved by the proposed model. ...

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  • The goal of the project is to enhance the database of the Oxford Dictionary of English (a forthcoming new edition of the 1998 New Oxford Dictionary of English) so that it contains not only the original dictionary content but also additional sets of data formalizing, codifying, and supplementing this content. This will allow the dictionary to be exploited effectively as a resource for computational applications. The Oxford Dictionary of English (ODE) is a high-level dictionary intended for fluent English speakers (especially native speakers) rather than for learners.

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  • A major focus of current work in distributional models of semantics is to construct phrase representations compositionally from word representations. However, the syntactic contexts which are modelled are usually severely limited, a fact which is reflected in the lexical-level WSD-like evaluation methods used.

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  • During early language acquisition, infants must learn both a lexicon and a model of phonetics that explains how lexical items can vary in pronunciation—for instance “the” might be realized as [Di] or [D@]. Previous models of acquisition have generally tackled these problems in isolation, yet behavioral evidence suggests infants acquire lexical and phonetic knowledge simultaneously.

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  • Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This paper introduces a novel sentence processing model that consists of a parser augmented with a probabilistic logic-based model of coreference resolution, which allows us to simulate how context interacts with syntax in a reading task. Our simulations show that a Weakly Interactive cognitive architecture can explain data which had been provided as evidence for the Strongly Interactive hypothesis. ...

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  • It has previously been assumed in the psycholinguistic literature that finite-state models of language are crucially limited in their explanatory power by the locality of the probability distribution and the narrow scope of information used by the model. We show that a simple computational model (a bigram part-of-speech tagger based on the design used by Corley and Crocker (2000)) makes correct predictions on processing difficulty observed in a wide range of empirical sentence processing data. ...

    pdf8p hongvang_1 16-04-2013 17 2   Download

  • We propose a computational model of text reuse tailored for ancient literary texts, available to us often only in small and noisy samples. The model takes into account source alternation patterns, so as to be able to align even sentences with low surface similarity. We demonstrate its ability to characterize text reuse in the Greek New Testament.

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  • This paper describes a noisy channel model of speech repairs, which can identify and correct repairs in speech transcripts. A syntactic parser is used as the source model, and a novel type of TAG-based transducer is the channel model. The use of TAG is motivated by the intuition that the reparandum is a “rough copy” of the repair. The model is trained and tested on the Switchboard disfluency-annotated corpus.

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  • This paper presents a novel statistical model for automatic identification of English baseNP. It uses two steps: the Nbest Part-Of-Speech (POS) tagging and baseNP identification given the N-best POS-sequences. Unlike the other approaches where the two steps are separated, we integrate them into a unified statistical framework. Our model also integrates lexical information. Finally, Viterbi algorithm is applied to make global search in the entire sentence, allowing us to obtain linear complexity for the entire process. ...

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  • Existing models of plan inference (PI) in conversation have assumed that the agent whose plan is being inferred (the actor) and the agent drawing the inference (the observer) have identical beliefs about actions in the domain. I argue that this assumption often results in failure of both the PI process and the communicative process that PI is meant to support. In particular, it precludes the principled generation of appropriate responses to queries that arise from invalid plans. I describe a model of P1 that abandons this assumption. It rests on an analysis of plans as mental phenomena.

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  • In this paper we present the tormal processing model of CLG, which has been influenced by the Constraint Logic Programming paradigm 18] 191.

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  • Automatic processing of metaphor can be clearly divided into two subtasks: metaphor recognition (distinguishing between literal and metaphorical language in a text) and metaphor interpretation (identifying the intended literal meaning of a metaphorical expression). Both of them have been repeatedly addressed in NLP. This paper is the first comprehensive and systematic review of the existing computational models of metaphor, the issues of metaphor annotation in corpora and the available resources. ...

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  • We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of linear constituency. The product model outperforms both components on their respective evaluation metrics, giving the best published figures for unsupervised dependency parsing and unsupervised constituency parsing. We also demonstrate that the combined model works and is robust cross-linguistically, being able to exploit either attachment or distributional regularities that are salient in the data. ...

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  • An investment of effort over the last two years has begun to produce a wealth of data concerning computational psycholinguistic models of syntax acquisition. The data is generated by running simulations on a recently completed database of word order patterns from over 3,000 abstract languages. This article presents the design of the database which contains sentence patterns, grammars and derivations that can be used to test acquisition models from widely divergent paradigms.

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  • This paper presents a tripartite model of dialogue in which three different kinds of actions are modeled: domain actions, problem-solving actions, and discourse or communicative actions. We contend that our process model provides a more finely differentiated representation of user intentions than previous models; enables the incremental recognition of communicative actions that cannot be recognized from a single utterance alone; and accounts for implicit acceptance of a communicated proposition. ...

    pdf8p bunmoc_1 20-04-2013 9 1   Download

  • We present an approach to grammar development where the task is decomposed into two separate subtasks. The first task is hnguistic, with the goal of producing a set of rules that have a large coverage (in the sense that the correct parse is among the proposed parses) on a bhnd test set of sentences. The second task is statistical, with the goal of developing a model of the grammar which assigns maximum probability for the correct parse.

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  • AMBER is a model of first language acquisition that improves its performance through a process of error recovery. The model is implemented as an adaptive production system that introduces new condition-action rules on the basis of experience. AMBER starts with the ability to say only one word at a time, but adds rules for ordering goals and producing grammatical morphemes, based on comparisons between predicted and observed sentences.

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  • We outline a model of generation with revision, focusing on improving textual coherence. We argue that high quality text is more easily produced by iteratively revising and regenerating, as people do, rather than by using an architecturally more complex single pass generator. As a general area of study, the revision process presents interesting problems: Recognition of flaws in text requires a descriptive theory of what constitutes well written prose and a parser which can build a representation in those terms. Improving text requires associating flaws with strategies for improvement.

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  • In this paper, I describe how Donnellan's distinction between referential and attributive uses of definite descriptions should be represented in a computational model of reference. After briefly discussing the significance of Donnellan's distinction, I reinterpret it as being three-tiered, relating to object representation, referring intentions, and choice of rehrring expression. I then present a cognitive model of referring, the components of which correspond to this analysis, and discuss the interaction that takes place among those components.

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