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Deriving frequency effects from biases in learning
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In: Proceedings of the Linguistic Society of America; Vol 6, No 1 (2021): Proceedings of the Linguistic Society of America; 514–525 ; 2473-8689 (2021)
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Unsupervised Formal Grammar Induction with Confidence
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In: Proceedings of the Society for Computation in Linguistics (2020)
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When lexical statistics and the grammar conflict: learning and repairing weight effects on stress.
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Constraints in contact: Animacy in English and Afrikaans genitive variation – a cross-linguistic perspective
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In: Glossa: a journal of general linguistics; Vol 2, No 1 (2017); 72 ; 2397-1835 (2017)
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Probabilistic Grammar: The view from Cognitive Sociolinguistics
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In: Glossa: a journal of general linguistics; Vol 2, No 1 (2017); 62 ; 2397-1835 (2017)
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Lexical Structure, Weightedness, And Information In Sentence Processing
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Intégration des données d'un lexique syntaxique dans un analyseur syntaxique probabiliste
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In: Penser le Lexique-Grammaire. Perspectives actuelles ; 30th International Conference on Lexis and Grammar (LGC'11) ; https://hal-upec-upem.archives-ouvertes.fr/hal-00621647 ; Fryni Kakoyianni-Doa. Penser le Lexique-Grammaire. Perspectives actuelles, Honoré Champion, pp.505-516, 2014, Collection Colloques, congrès et conférences. Sciences du Langage, histoire de la langue et des dictionnaires. 30th International Conference on Lexis and Grammar, Nicosia, Cyprus, 2011, 978-2-7453-2512-9 (2014)
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MSEE: Stochastic Cognitive Linguistic Behavior Models for Semantic Sensing
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In: DTIC (2013)
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Abstract:
This report summarizes the major findings from our research on a semantic information representation framework (SIRF) for visual sensing scenarios. First, the concept and architecture of a cognitive linguistic (CL) based SIRF is introduced. Two levels of information abstraction are proposed within this framework. At the syntactic level, a probabilistic contest free grammar (PCFG) method is employed for information compression and summarization. At the semantic level, a Bayesian network approach is used to achieve semantic concept inference and reasoning. To facilitate the functions of this SIRF, several conceptual primitive modeling methods are proposed, which include a dynamic structure preserving map (DSPM) for individual human action recognition, a Gaussian Process Dynamic Model with Social Network Analysis (GPDM-SNA) for a small human group action recognition, an extended GPDM-SNA method for human object interaction (HOI) recognition, and a pyramid histogram of gradient (pHOG) method for human object recognition based on gait images. In addition to these conceptual primitive models, two quantities sensing modality utility assessment methods are introduced. They are essentially feature selection methods, one is based sparse imputation and one is based on 11 graph. Extensive experiments on publicly available datasets have been conducted to assess the effectiveness of the proposed methods, and highly competitive and promising results have been observed.
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Keyword:
*RECOGNITION; *VIDEO IMAGES; BAYESIAN NETWORK; COGNITION; COGNITIVE LINGUISTICS; CONTEXT FREE GRAMMARS; Cybernetics; DETECTORS; GAIT RECOGNITION; GROUP ACTION RECOGNITION; HUMAN OBJECT INTERACTION; LEARNING MACHINES; LINGUISTICS; MACHINE LEARNING; OPTICAL DETECTION; PE61101E; PROBABILISTIC CONTEXT FREE GRAMMAR; SEMANTIC INFORMATION REPRESENTATION; SEMANTICS; SENSOR DATA; SENSOR UTILITY METRICS; SPARSE CODING; VISUAL SENSING; WUAFRL1000Y02C
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA589989 http://www.dtic.mil/docs/citations/ADA589989
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Detecting grammatical errors with treebank-induced, probabilistic parsers
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In: Wagner, Joachim orcid:0000-0002-8290-3849 (2012) Detecting grammatical errors with treebank-induced, probabilistic parsers. PhD thesis, Dublin City University. (2012)
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Techniques for utterance disambiguation in a human-computer dialogue system
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Integration of Data from a Syntactic Lexicon into Generative and Discriminative Probabilistic Parsers
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In: International conference on Recent Advances in Natural Language Processing (RANLP'11) ; https://hal-upec-upem.archives-ouvertes.fr/hal-00621646 ; International conference on Recent Advances in Natural Language Processing (RANLP'11), 2011, Hissar, Bulgaria. pp.363-370 (2011)
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Incremental Syntactic Language Models for Phrase-Based Translation
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In: DTIC (2011)
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From Exemplar to Grammar: A Probabilistic Analogy-based Model of Language Learning
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In: http://staff.science.uva.nl/~rens/analogy.pdf (2009)
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