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LitCrit: exploring intentions as a basis for automated feedback on Related Work.
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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances
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In: International journal of semantic computing, 14 (2), 249–272 ; ISSN: 1793-351X, 1793-7108 (2020)
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Discovering and analysing lexical variation in social media text
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Modelling speaker adaptation in second language learner dialogue
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Personal-ITY: A novel youtube-based corpus for personality prediction in Italian
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Stop the Morphological Cycle, I Want to Get Off: Modeling the Development of Fusion
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In: Proceedings of the Society for Computation in Linguistics (2020)
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Abstract:
Historical linguists observe that many fusional (unsegmentable) morphological structures developed from agglutinative (segmentable) predecessors. Such changes may result when learners fail to acquire a phonological alternation, and instead, “chunk” the altered versions of morphemes and memorize them as underlying representations. We present a Bayesian model of this process, which learns which morphosyntactic properties are chunked together, what their underlying representations are, and what phonological processes apply to them. In simulations using artificial data, we provide quantitative support to two claims about agglutinative and fusional structures: that optional morphological markers discourage fusion from developing, but that stress-based vowel reduction encourages it.
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Keyword:
agglutination; computational linguistics; diachronic change; fusion; morphology
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URL: https://scholarworks.umass.edu/scil/vol3/iss1/40 https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1134&context=scil
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108 |
Defining distinctiveness: A computational and experimental analysis
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Are They There Yet? Revisiting the Accuracy Level of Computer-Generated Translation
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In: Journal Polingua: Scientific Journal of Linguistics, Literature and Education, Vol 9, Iss 1, Pp 1-4 (2020) (2020)
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110 |
Variables Must be Limited to a Single Feature
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In: Proceedings of the Annual Meetings on Phonology; Proceedings of the 2019 Annual Meeting on Phonology ; 2377-3324 (2020)
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Learning to Parse Grounded Language using Reservoir Computing
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In: ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics ; https://hal.inria.fr/hal-02422157 ; ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, Aug 2019, Olso, Norway. ⟨10.1109/devlrn.2019.8850718⟩ ; https://ieeexplore.ieee.org/abstract/document/8850718 (2019)
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Statistische Modelle für die hierarchische phrasenbasierte maschinelle Übersetzung ... : Statistical models for hierarchical phrase-based machine translation ...
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Methods for taking semantic graphs apart and putting them back together again ...
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Proposition-based summarization with a coherence-driven incremental model ...
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Fang, Yimai. - : Apollo - University of Cambridge Repository, 2019
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Dated Phylogenies Shed Light on the ancestry of Sino-Tibetan languages ...
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A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics ...
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Dated Phylogenies Shed Light on the ancestry of Sino-Tibetan languages ...
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Ground truth for Neue Zürcher Zeitung black letter period ...
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Source code and data accompanying the paper «An automated framework for fast cognate detection and Bayesian phylogenetic inference in computational historical linguistics» ...
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