Proceedings of the Annual Meeting of the Cognitive Science Society

I present a computational-level model of language production in terms of a combination of information theory and control theory in which words are chosen incrementally in order to maximize communicative value subject to an information-theoretic capacity constraint. The theory generally predicts a tradeoff between ease of production and communicative accuracy. I apply the theory to two cases of apparent availability effects in language production, in which words are selected on the basis of their accessibility to a speaker who has not yet perfectly planned the rest of the utterance. Using corpus data on English relative clause complementizer dropping from Levy & Jaeger (2007) and experimental data on Mandarin noun classifier choice from Zhan & Levy (2019), I show that the theory reproduces the observed phenomena, providing an alternative account to Uniform Information Density (UID) and a promising general model of language production which is tightly linked to emerging theories in computational neuroscience.