A psycholinguistic model of natural language parsing implemented in simulated neurons.
Huyck, Christian R. (2009) A psycholinguistic model of natural language parsing implemented in simulated neurons. Cognitive Neurodynamics, 3 (4). pp. 316-330. ISSN 1871-4080
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A natural language parser implemented entirely in simulated neurons is described. It produces a semantic representation based on frames. It parses solely using simulated fatiguing Leaky Integrate and Fire neurons, that are a relatively accurate biological model that is simulated efficiently. The model works on discrete cycles that simulate 10 ms. of biological time, so the parser has a simple mapping to psychological parsing time. Comparisons to human parsing studies show that the parser closely approximates this data. The parser makes use of Cell Assemblies and the semantics of lexical items is represented by overlapping hierarchical Cell Assemblies so that semantically related items share neurons. This semantic encoding is used to resolve prepositional phrase attachment ambiguities encountered during parsing. Consequently, the parser provides a neurally-based cognitive model of parsing.
|Research Areas:||Middlesex University Schools and Centres > School of Science and Technology > Computer Science|
Middlesex University Schools and Centres > School of Science and Technology > Computer Science > Artificial Intelligence group
|Citations on ISI Web of Science:||1|
|Deposited On:||02 Mar 2010 14:41|
|Last Modified:||01 Nov 2014 03:53|
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