A Computational Model of Auditory Perceptual Learning: Predicting Learning Interference Across Multiple Tasks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work we build a computational model of several auditory perceptual learning experiments. The modeled experiments show a pattern of learning interference which may help shed light on the structure of both short and long term stores of perceptual memory. It is our hypothesis that the observed interference patterns can be explained by the relationship of stimuli across tasks and how these relationships interact with the limits of human memory. We account for the fact that information is shared across tasks in our model through use of methodology from the machine learning community on transfer learning. When we introduce a set of plausible limits on memory, such a model demonstrates the same pattern of learning interference observed in the human experiments.

Original languageEnglish (US)
Title of host publicationExpanding the Space of Cognitive Science - Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, CogSci 2011
EditorsLaura Carlson, Christoph Hoelscher, Thomas F. Shipley
PublisherThe Cognitive Science Society
Pages1031-1036
Number of pages6
ISBN (Electronic)9780976831877
StatePublished - 2011
Event33rd Annual Meeting of the Cognitive Science Society: Expanding the Space of Cognitive Science, CogSci 2011 - Boston, United States
Duration: Jul 20 2011Jul 23 2011

Publication series

NameExpanding the Space of Cognitive Science - Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, CogSci 2011

Conference

Conference33rd Annual Meeting of the Cognitive Science Society: Expanding the Space of Cognitive Science, CogSci 2011
Country/TerritoryUnited States
CityBoston
Period7/20/117/23/11

Keywords

  • Acquisition
  • Consolidation
  • Learning Interference
  • Perceptual Learning
  • Perceptual Memory
  • Transfer Learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Fingerprint

Dive into the research topics of 'A Computational Model of Auditory Perceptual Learning: Predicting Learning Interference Across Multiple Tasks'. Together they form a unique fingerprint.

Cite this