Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue
Thomas P. Utting University of Aberdeen, Mario Giulianelli University College London, University of London, Arabella Sinclair
原文摘要
We model utterance production as probabilistic cost-sensitive choice over contextual alternatives, using information-theoretic notions of cost. We distinguish between goal-directed alternatives that realise a fixed communicative intent and goal-agnostic alternatives defined only by contextual plausibility, allowing us to derive speaker- and listener-oriented interpretations of different cost measures. We present a procedure to generate both types of alternative sets using language models. Analysing production choices in open-ended dialogue under both deterministic and noisy cost minimisation, we find that surprisal minimisation relative to goal-directed alternatives provides the strongest explanation of production choices. Uniformity-based costs show weaker overall predictive power, but their influence increases markedly when evaluated relative to goal-agnostic alternatives, consistent with listener-oriented accounts. More broadly, our study suggests that alternative-conditioned optimisation with LM-generated alternatives provides a principled framework for studying speaker and listener pressures in naturalistic language production.
cs.CL
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2026 · 正式发表