Saving the ‘Live’: Performance and cultural Heritage

Both humans and Large Language Models (LMs) generate predictions about upcoming words and structures based on recent context. In dialogue, speakers continuously choose how to realise their communicative intentions, with these choices shaped by multiple, sometimes competing pressures, including production costs borne by the speaker and comprehension costs incurred by the listener. Production costs reflect the effort involved in planning and generating an utterance, while comprehension costs reflect how easily an utterance can be processed and interpreted. These costs are influenced by a range of factors, including priming, utterance length, informational content, and contextual predictability.

In this talk, Arabella Sinclair explores how LMs can serve both as tools for studying human interaction and as components of broader cognitive models of language processing.