Neurocognitive models of crossmodal language learning (C04)

• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing ; General, Cognitive and Mathematical Psychology ; Human Cognitive and Systems Neuroscience
• Term: since 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 261402652

The Project will focus on the research question of how to build a neural cognitive model that integrates embodied and knowledge-based crossmodal information into language learning. The goals include the realisation of large-scale embodied and disembodied data collections, the investigation of neurocognitive mechanisms in computational models as well as data-driven representation models for language learning, and the integration and study of crossmodal models for large-scale technical systems. In particular, the project will examine a variety of language functions inspired by the processing in the human brain, study representation learning architectures for language learning from large-scale data and knowledge bases, and transfer them into prototypes for human-robot interaction.

• DFG Programme: CRC/Transregios
• Subproject of: TRR 169: Crossmodal Learning: Adaptivity, Prediction and Interaction
• International Connection: China
• Applicant Institution: Universität Hamburg
• Project Heads: Professor Dr. Zhiyuan Liu; Dr. Cornelius Weber; Professor Dr. Stefan Wermter