Modelling the effects of semantic ambiguity in word recognition

Cognitive Science 28 (1):89-104 (2004)
  Copy   BIBTEX


Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The model performs well on the task of retrieving the different meanings of ambiguous words, and is able to simulate data reported by Rodd, Gaskell, and Marslen‐Wilson [J. Mem. Lang. 46 (2002) 245] on how semantic ambiguity affects lexical decision performance. In particular, the network shows a disadvantage forwords with multiple unrelated meanings (e.g., bark) that coexists with a benefit for words with multiple related word senses (e.g., twist). The ambiguity disadvantage arises because of interference between the different meanings, while the sense benefit arises because of differences in the structure of the attractor basins formed during learning. Words with few senses develop deep, narrow attractor basins, while words with many senses develop shallow, broad basins. We conclude that the mental representations of word meanings can be modelled as stable states within a high‐dimensional semantic space, and that variations in the meanings of words shape the landscape of this space.



    Upload a copy of this work     Papers currently archived: 91,252

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Lexical semantics without thematic roles.Yael Ravin - 1990 - New York: Oxford University Press.
Ambiguity.Kent Bach - manuscript
It's good . . . But is it ART?Paul A. Luce, Stephen D. Goldinger & Michael S. Vitevitch - 2000 - Behavioral and Brain Sciences 23 (3):336-336.
Semantic interpretation and the resolution of ambiguity.Graeme Hirst - 1987 - New York: Cambridge University Press.


Added to PP

32 (#476,543)

6 months
5 (#565,734)

Historical graph of downloads
How can I increase my downloads?