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The hidden dangers of computer modelling

Remarks on Sokolik and Smith's connectionist learning model of French gender

Datos Bibliográficos

ID11655643
AutoresSusanne E Carroll (University of Potsdam), Susanne Carroll (0000-0002-4157-6677, University of Potsdam, autor de correspondencia)
Año1995
Volumen11
Número3
Páginas193-205
Fecha de publicación1995-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSecond language Research (JOURNAL)
Identificadores de la revistaISSN: 0267-6583 • E-ISSN: 1477-0326
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1177/026765839501100301
OpenAlexW2049362884
IdiomaEN
Citas recibidas13
Referencias citadas13

Sokolik and Smith (1992) conducted three computer modelling experiments involving the learning of French gender attribution using a connectionist architecture. Their device learns to classify nouns quickly, given only letter-plus-position information about word spellings and feedback about the match between the target and the device's output. In particular, the device is not programmed with rules nor does it acquire any. Sokolik and Smith conclude that their model of gender attribution and the acquisition thereof has relevance for SLA. In these remarks, I show why this conclusion is wrong

Artificial neural network · Attribution · Cognitive science · Connectionism · Language acquisition · Linguistics · Natural language processing · Noun · Relevance (law · Word (group theory · Child and Animal Learning Development · Computer Science · Language and cultural evolution · Philosophy · Psychology · Social Psychology · Speech and dialogue systems · Artificial Intelligence

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Obras citantes distintas13
Citas por año0,43
Intervalo de citas1996 - 2013 (18)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 13
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