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Comparing MOSAIC and the variational learning model of the optional infinitive stage in early child language
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On the Utility of Conjoint and Compositional Frames and Utterance
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Understanding the Developmental Dynamics of Subject Omission: The Role of Processing Limitations in Learning
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Simulating the Noun-Verb Asymmetry in the Productivity of Children’s Speech
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Linking working memory and long-term memory: A computational model of the learning of new words
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Jones, G; Gobet, F; Pine, J M. - : Blackwell Publishing. The definitive version is available at onlinelibrary.wiley.com, 2007
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8 |
Modelling the Development of Children’s use of Optional Infinitives in Dutch and English using MOSAIC
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9 |
Unifying cross-linguistic and within-language patterns of finiteness marking in MOSAIC
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10 |
Simulating the cross-linguistic development of optional infinitive errors in MOSAIC.
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11 |
Simulating optional infinitive errors in child speech through the omission of sentence-internal elements.
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Resolving ambiguities in the extraction of syntactic categories through chunking.
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Abstract:
In recent years, several authors have investigated how co-occurrence statistics in natural language can act as a cue that children may use to extract syntactic categories for the language they are learning. While some authors have reported encouraging results, it is difficult to evaluate the quality of the syntactic categories derived. It is argued in this paper that traditional measures of accuracy are inherently flawed. A valid evaluation metric needs to consider the well-formedness of utterances generated through a production end. This paper attempts to evaluate the quality of the categories derived from cooccurrence statistics through the use of MOSAIC, a computational model of syntax acquisition that has already been used to simulate several phenomena in child language. It will be shown that derived syntactic categories which may appear to be of high quality will quickly give rise to errors which are not typical of child speech. A solution to this problem is suggested in the form of a chunking mechanism which serves to differentiate between alternative grammatical functions of identical word forms. Results are evaluated in terms of the error rates in utterances produced by the system as well as the quantitative fit to the phenomenon of subject omission.
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Keyword:
child language; chunking; co-occurrence statistics; computational modelling; error; language acquisition; MOSAIC; subject omission; syntax
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URL: http://bura.brunel.ac.uk/handle/2438/779
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13 |
Simulating the temporal reference of Dutch and English Root Infinitives.
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14 |
Modelling syntactic development in a cross-linguistic context
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The role of input size and generativity in simulating language acquisition.
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Modelling children's negation errors using probabilistic learning in MOSAIC.
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17 |
Modelling the development of Dutch Optional Infinitives in MOSAIC.
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Subject omission in children's language; The case for performance limitations in learning.
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Modeling the optional infinite stage in MOSAIC: A generalization to Dutch
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