Colloquium: Natural Language Acquisition in Recurrent Neural Architectures

20 June 2016

Our understandings of the behavioural and mechanistic characteristics for natural language are still in its infancy and we need to bridge the gap between the insights from linguistics, neuroscience, and behavioural psychology. To contribute an understanding of the appropriate characteristics in a brain-inspired neural architecture that favour language acquisition, recurrent neural models have been developed for embodied and multi-modal language processing, embedded in a developmental robotics framework. In this dissertation, the main contributions from the study of these models are reported.

Monday, 20. June 2016, 14:00, Informatik, Room D-220

Stefan Heinrich, University of Hamburg