The Learnability of the Wh-Island Constraint in Dutch by a Long Short-Term Memory Network

The current study investigates whether a Long Short-Term Memory (LSTM) network can learn the wh-island constraint in Dutch in a way comparable to human native speakers. After establishing with an acceptability judgement task that native speakers demonstrate a clear sensitivity to wh-island violations, the LSTM network was tested on the same sentences. Contrary to the results of the native speakers, the network was not able to recognize wh-islands and to block gap expectancies within them. This suggests that input and the network’s inductive biases alone might not be enough to learn about synta... Mehr ...

Verfasser: Suijkerbuijk, Michelle
Frank, Stefan L.
de Swart, Peter
Dokumenttyp: posted-content
Erscheinungsdatum: 2023
Verlag/Hrsg.: Center for Open Science
Sprache: unknown
Permalink: https://search.fid-benelux.de/Record/base-27469723
Datenquelle: BASE; Originalkatalog
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Link(s) : http://dx.doi.org/10.31234/osf.io/njr3z

The current study investigates whether a Long Short-Term Memory (LSTM) network can learn the wh-island constraint in Dutch in a way comparable to human native speakers. After establishing with an acceptability judgement task that native speakers demonstrate a clear sensitivity to wh-island violations, the LSTM network was tested on the same sentences. Contrary to the results of the native speakers, the network was not able to recognize wh-islands and to block gap expectancies within them. This suggests that input and the network’s inductive biases alone might not be enough to learn about syntactic island constraints, and that built-in language knowledge or abilities might be necessary.