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Structural Priming and the Mental Representation of Agentive and Temporal by-Phrase Constructions: An Eye-Tracking Study
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Structural Priming and the Mental Representation of Agentive and Temporal by-Phrase Constructions: An Eye-Tracking Study ...
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CROSS-LINGUISTIC DIFFERENCES IN THE LEARNING OF INFLECTIONAL MORPHOLOGY: EFFECTS OF TARGET LANGUAGE PARADIGM COMPLEXITY ...
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CROSS-LINGUISTIC DIFFERENCES IN THE LEARNING OF INFLECTIONAL MORPHOLOGY: EFFECTS OF TARGET LANGUAGE PARADIGM COMPLEXITY
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Issues in L2 phonological processing ; Questions sur le traitement phonologique en langue seconde
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In: https://tel.archives-ouvertes.fr/tel-02304656 ; Linguistics. Université Paris sciences et lettres, 2019. English. ⟨NNT : 2019PSLEE007⟩ (2019)
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Acquisition d'une langue visuo-spatiale et plurilinguisme audio-oral : le cas de l'American Sign Language (ASL) en tant que L2 selon la perception d'apprenants en milieu universitaire
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Representing linguistic knowledge with probabilistic models
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In: Meylan, Stephan Charles. (2018). Representing linguistic knowledge with probabilistic models. UC Berkeley: Psychology. Retrieved from: http://www.escholarship.org/uc/item/5vp920sn (2018)
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Abstract:
The use of language is one of the defining features of human cognition. Focusing here on two key features of language, productivity and robustness, I examine how basic questions regarding linguistic representation can be approached with the help of probabilistic generative language models, or PGLMs. These statistical models, which capture aspects of linguistic structure in terms of distributions over events, can serve as both the product of language learning and as prior knowledge in real-time language processing. In the first two chapters, I show how PGLMs can be used to make inferences about the nature of people's linguistic representations. In Chapter 1, I look at the representations of language learners, tracing the earliest evidence for a noun category in large developmental corpora. In Chapter 2, I evaluate broad-coverage language models reflecting contrasting assumptions about the information sources and abstractions used for in-context spoken word recognition in their ability to capture people's behavior in a large online game of “Telephone.” In Chapter 3, I show how these models can be used to examine the properties of lexicons. I use a measure derived from a probabilistic generative model of word structure to provide a novel interpretation of a longstanding linguistic universal, motivating it in terms of cognitive pressures that arise from communication. I conclude by considering the prospects for a unified, expectations-oriented account of language processing and first language learning.
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Keyword:
Bayesian inference; Cognitive psychology; Computer science; information theory; language acquisition; language models; Linguistics; probabilistic generative models; psycholinguistics
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URL: http://www.escholarship.org/uc/item/5vp920sn
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Relating lexical and syntactic processes in language: Bridging research in humans and machines ...
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Relating lexical and syntactic processes in language: Bridging research in humans and machines
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An Exploration of the Relationship Between Event Meaning and Syntactic Structure
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In: Gruberg, Nicholas. (2017). An Exploration of the Relationship Between Event Meaning and Syntactic Structure. UC San Diego: Psychology. Retrieved from: http://www.escholarship.org/uc/item/9s09j34r (2017)
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Language Science Meets Cognitive Science: Categorization and Adaptation ...
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Schema-guided comprehension of noun-noun compounds: An experimental and corpus-based approach
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Measuring syntactic complexity in the academic writing of English students at the University of Vienna
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The Role of Morphology in Word Recognition of Hebrew as a Templatic Language
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Language Science Meets Cognitive Science: Categorization and Adaptation
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