Multimodal language learning and representation: Neurocognitive and computational mechanisms

Activity: Talk or presentationInvited talk


In an era of rapid developments in digital technology and generative AI, we need to examine the mechanisms of language learning and representation from an integrative neurocomputational perspective. In this talk, I outline an approach that combines emerging technologies and data-driven methodologies with current neurocomputational theories, with particular reference to embodied language learning. I will discuss in particular the neurocomputational mechanisms underlying child and adult language learning, and the computational methods that enable us to extend our studies to new frontiers. First, we will examine how human learners effectively integrate multimodal information in a social interactive context, and how this contrasts with generative AI systems such as large language models (LLMs). Second, we will identify neurocognitive mechanisms underlying individual differences in native and non-native speakers during the processing of language in naturalistic contexts. Finally, we will examine how L2 learners can acquire a language in a similar way as L1 speakers when learning is enabled by technology-enhanced immersive situations. Our studies highlights context-based communicative abilities so that we can develop personalized pedagogical designs that tailor to individual learners’ needs and learning profiles.

Period21 Jun 2024
Event titleSixth International Conference on Linguistics and Language Studies
Event typeConference
LocationChinaShow on map
Degree of RecognitionInternational