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Hits 1 – 14 of 14

1
Learning Argument Structures with Recurrent Neural Network Grammars
In: Proceedings of the Society for Computation in Linguistics (2022)
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2
Cross-linguistic patterns of morpheme order reflect cognitive biases: An experimental study of case and number morphology ...
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3
Modeling Human Sentence Processing with Left-Corner Recurrent Neural Network Grammars ...
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4
Modeling Human Sentence Processing with Left-Corner Recurrent Neural Network Grammars ...
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5
Effective Batching for Recurrent Neural Network Grammars ...
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6
Lower Perplexity is Not Always Human-Like ...
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7
Lower Perplexity is Not Always Human-Like ...
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8
Modeling Human Morphological Competence
In: Front Psychol (2020)
Abstract: One of the central debates in the cognitive science of language has revolved around the nature of human linguistic competence. Whether syntactic competence should be characterized by abstract hierarchical structures or reduced to surface linear strings has been actively debated, but the nature of morphological competence has been insufficiently appreciated despite the parallel question in the cognitive science literature. In this paper, in order to investigate whether morphological competence should be characterized by abstract hierarchical structures, we conducted a crowdsourced acceptability judgment experiment on morphologically complex words and evaluated five computational models of morphological competence against human acceptability judgments: Character Markov Models (Character), Syllable Markov Models (Syllable), Morpheme Markov Models (Morpheme), Hidden Markov Models (HMM), and Probabilistic Context-Free Grammars (PCFG). Our psycholinguistic experimentation and computational modeling demonstrated that “morphous” computational models with morpheme units outperformed “amorphous” computational models without morpheme units and, importantly, PCFG with hierarchical structures most accurately explained human acceptability judgments on several evaluation metrics, especially for morphologically complex words with nested morphological structures. Those results strongly suggest that human morphological competence should be characterized by abstract hierarchical structures internally generated by the grammar, not reduced to surface linear strings externally attested in large corpora.
Keyword: Psychology
URL: https://doi.org/10.3389/fpsyg.2020.513740
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688581/
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9
Modeling Morphological Processing in Human Magnetoencephalography
In: Proceedings of the Society for Computation in Linguistics (2020)
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10
Dual suppletion in Japanese
In: Proceedings of the 14th Workshop on Altaic Formal Linguistics (WAFL14) ([2019]), S. 193-204
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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11
Case-Number morpheme order ...
Saldana, Carmen; Oseki, Yohei; Culbertson, Jennifer. - : Open Science Framework, 2019
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12
Some consequences of simplest Merge and defectiveness in Japanese
In: Proceedings of the 10th Workshop on Altaic Formal Linguistics (WAFL10) ([2018]), S. 217-228
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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13
The reliability of acceptability judgments across languages
In: Glossa: a journal of general linguistics; Vol 3, No 1 (2018); 100 ; 2397-1835 (2018)
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14
Wh-Concord in Okinawan = Syntactic Movement + Morphological Merger
In: University of Pennsylvania Working Papers in Linguistics (2016)
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