Predicting Movement Alignment and Back-Channeling in Conversational Dyads using Large Language Model (LLM) Embeddings

Develop a model that predicts movement alignment between speakers and listeners based on LLM-derived contextual embeddings.
Develop a model than predicts listener back-channelling gestures reflecting comprehension based on the semantic content of the conversation