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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Sensorimotor cognition and natural language syntax Knott, Alistair. - Cambridge, Mass. [u.a.] : The MIT Press, 2012 Leibniz-Zentrum Allgemeine Sprachwissenschaft Show details 2 Sensorimotor cognition and natural language syntax Knott, Alistair. - Cambridge, Massachusetts : MIT Press, 2012, [2012]©2012 MPI für Psycholinguistik Show details 3 Sensorimotor cognition and natural language syntax Knott, Alistair. - Cambridge, Mass. [u.a.] : MIT Press, 2012 MPI-SHH Linguistik Show details 4 Mapping sensorimotor sequences to word sequences: a connectionist model of language acquisition and sentence generation Takac, Martin; Knott, Alistair; Benuskova, Lubica In: Cognition. - Amsterdam [u.a] : Elsevier 125 (2012) 2, 288-308 BLLDB OLC Linguistik Show details 5 Sensorimotor cognition and natural language syntax Knott, Alistair. - Cambridge, Mass. [u.a.] : MIT Press, 2012 BLLDB UB Frankfurt Linguistik Show details 6 Pragmatic Bootstrapping: A Neural Network Model of Vocabulary Acquisition Caza, Gregory A.; Knott, Alistair In: Language learning and development. - Philadelphia, Pa. : Taylor & Francis 8 (2012) 2, 113-135 OLC Linguistik Show details 7 Techniques for utterance disambiguation in a human-computer dialogue system Lurcock, Pontus Conrad. - : University of Otago, 2012 BASE Show details 8 A Statistical Model of Error Correction for Computer Assisted Language Learning Systems Basiron, Halizah. - : University of Otago, 2012 Abstract: This thesis presents a study in the area of computer assisted language learning systems. The study focusses on the topic of automatic correction of student errors. In the thesis, I will describe a novel statistical model of error correction, trained on a newly gathered corpus of language data from Malaysian EFL learners, and tested on a different group of students from the same population. The main novelty of my statistical model is that it explicitly represents 'corrections' -- i.e. circumstances where a language teacher corrects a student's language. Most statistical models used in language learning applications are simply models of the target language being taught; their aim is just to define the kinds of sentence which are expected in the target language. These models are good at recognising when a student's utterance contains an error: any sentence which is sufficiently improbable according to a model of the target language can be hypothesised to contain an error. But they are not so good at providing suggestions about how to correct errors. In any student's sentence, there are many things which could be changed: the space of possible corrections is too large to be exhaustively searched. A statistical system which explicitly models the incidence of corrections can help guide the search for good corrections. The system which I describe in this thesis learns about the kinds of context in which particular corrections are made, and after training, is able to make quite good suggestions about how to correct sentences containing errors. Keyword: computer assisted language learning systems; language modeling; natural language processing URL: http://hdl.handle.net/10523/2291 BASE Hide details

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