Segmentation as Retention and Recognition: the R&R model
| Authors | |
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| Publication date | 2017 |
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| Book title | CogSci 2017 |
| Book subtitle | proceedings of the 39th Annual Meeting of the Cognitive Science Society : London, UK : 26-29 July 2017 : Computational Foundations of Cognition |
| ISBN (electronic) |
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| Event | 39th Annual Meeting of the Cognitive Science Society |
| Volume | Issue number | 2 |
| Pages (from-to) | 1531-1536 |
| Publisher | Austin, TX: Cognitive Science Society |
| Organisations |
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| Abstract | We present the Retention and Recognition model (R&R), a probabilistic exemplar model that accounts for segmentation in Artificial Language Learning experiments. We show that R&R provides an excellent fit to human responses in three segmentation experiments with adults (Frank et al., 2010), outperforming existing models. Additionally, we analyze the results of the simulations and propose alternative explanations for the experimental findings. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://cognitivesciencesociety.org/wp-content/uploads/2019/01/cogsci17_proceedings.pdf |
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