# The Computational Structure of Unintentional Meaning

## TL;DR

This paper presents a Bayesian model explaining how listeners interpret speech-acts with unintentional meanings, highlighting the complex reasoning involved in understanding both intended and unintended messages.

## Contribution

It introduces a novel Bayesian framework for modeling how listeners infer unintentional meanings in speech-acts, emphasizing perspective-taking and reasoning about context.

## Key findings

- Humans can distinguish between intentional and unintentional speech-acts.
- The model accurately predicts human judgments in vignette-based experiments.
- Understanding unintentional meaning involves sophisticated mental state reasoning.

## Abstract

Speech-acts can have literal meaning as well as pragmatic meaning, but these both involve consequences typically intended by a speaker. Speech-acts can also have unintentional meaning, in which what is conveyed goes above and beyond what was intended. Here, we present a Bayesian analysis of how, to a listener, the meaning of an utterance can significantly differ from a speaker's intended meaning. Our model emphasizes how comprehending the intentional and unintentional meaning of speech-acts requires listeners to engage in sophisticated model-based perspective-taking and reasoning about the history of the state of the world, each other's actions, and each other's observations. To test our model, we have human participants make judgments about vignettes where speakers make utterances that could be interpreted as intentional insults or unintentional faux pas. In elucidating the mechanics of speech-acts with unintentional meanings, our account provides insight into how communication both functions and malfunctions.