Computer Science – Computation and Language
Scientific paper
1996-05-13
Computer Science
Computation and Language
In proceedings of the 18th annual meeting of the Cognitive Science Society. 6 pages, 4 postscript figures. cmp-lg has trouble
Scientific paper
The German plural system has become a focal point for conflicting theories of language, both linguistic and cognitive. We present simulation results with three simple classifiers - an ordinary nearest neighbour algorithm, Nosofsky's `Generalized Context Model' (GCM) and a standard, three-layer backprop network - predicting the plural class from a phonological representation of the singular in German. Though these are absolutely `minimal' models, in terms of architecture and input information, they nevertheless do remarkably well. The nearest neighbour predicts the correct plural class with an accuracy of 72% for a set of 24,640 nouns from the CELEX database. With a subset of 8,598 (non-compound) nouns, the nearest neighbour, the GCM and the network score 71.0%, 75.0% and 83.5%, respectively, on novel items. Furthermore, they outperform a hybrid, `pattern-associator + default rule', model, as proposed by Marcus et al. (1995), on this data set.
Hahn Ulrike
Nakisa Ramin Charles
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