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One model for the learning of language.
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In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022)
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Computational Measures of Deceptive Language: Prospects and Issues
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In: ISSN: 2297-900X ; EISSN: 2297-900X ; Frontiers in Communication ; https://hal.archives-ouvertes.fr/hal-03629780 ; Frontiers in Communication, Frontiers, 2022, 7, pp.792378. ⟨10.3389/fcomm.2022.792378⟩ (2022)
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Animal linguistics in the making: the Urgency Principle and titi monkeys’ alarm system
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In: ISSN: 0394-9370 ; Ethology Ecology and Evolution ; https://hal.inrae.fr/hal-03518874 ; Ethology Ecology and Evolution, Taylor & Francis, 2022, pp.1-17. ⟨10.1080/03949370.2021.2015452⟩ (2022)
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A Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
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In: Journal of Open Humanities Data; Vol 8 (2022); 3 ; 2059-481X (2022)
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Using Machine Learning for Pharmacovigilance: A Systematic Review
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In: Pharmaceutics; Volume 14; Issue 2; Pages: 266 (2022)
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Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
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Hebrew Transformed: Machine Translation of Hebrew Using the Transformer Architecture
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| 12 |
Causal and Semantic Relations in L2 Text Processing: An Eye-Tracking Study
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Nahatame, Shingo. - : University of Hawaii National Foreign Language Resource Center, 2022. : Center for Language & Technology, 2022
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Abstract:
This study is an extension of Nahatame’s (2018) research that demonstrated the effects of causal and semantic relations between sentences on second language (L2) text processing. Employing eye tracking, this study aimed to examine whether these effects appear during more natural, uninterrupted reading processes and to identify the time course of the effects. In the experiment, Japanese learners of English read two-sentence texts that varied in their causal and semantic relatedness, as evaluated by crowdsourced human judgments and via a computational approach (latent semantic analysis), respectively. Two eye-movement measures were collected and analyzed: first-pass reading times for the second sentence and lookbacks from the second to the first sentence. The results indicated that causal relatedness had a robust impact on both reading times and lookbacks. However, semantic relatedness impacted only reading times, and its effects were modulated by causal relatedness. Theoretical, pedagogical, and methodological implications of this finding were discussed.
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Keyword:
coherence; computational linguistics; discourse processing; English as a Foreign Language (EFL); eye tracking; psycholinguistics; reading processes
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URL: http://hdl.handle.net/10125/67414
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| 13 |
Phylogenetic trees: Grammar versus vocabulary
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In: Russian Journal of Linguistics, Vol 26, Iss 1, Pp 31-50 (2022) (2022)
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| 14 |
French de and en as expressions of the genitive case: a unified analysis within LFG and computational implementation in XLE1
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In: DELTA: Documentação e Estudos em Linguística Teórica e Aplicada; v. 37 n. 1 (2021) ; 1678-460X ; 0102-4450 (2022)
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