Miller's monkey updated: Communicative efficiency and the statistics of words in natural language

Jordan Kodner, Spencer Caplan

Abstract: Is language designed for communicative and functional efficiency? G. K. Zipf famously argued that shorter words are more frequent because they are easier to use, thereby resulting in the statistical law that bears his name. Yet, G. A. Miller showed that even a monkey randomly typing at a keyboard, and intermittently striking the space bar, would generate “words” with similar statistical properties. Recent quantitative analyses of human language lexicons (Piantadosi et al., 2012) have revived Zipf's functionalist hypothesis. Ambiguous words tend to be short, frequent, and easy to articulate in language production. Such statistical findings are commonly interpreted as evidence for pressure for efficiency, as the context of language use often provides cues to overcome lexical ambiguity. In this study, we update Miller's monkey thought experiment to incorporate empirically motivated phonological and semantic constraints