Production expectations modulate contrastive inference

AbstractContrastive inferences, whereby a listener pragmatically infers a speaker's referential intention of a partial referring expression like "the yellow" by reasoning about other objects in the context, are notoriously unstable. We report a production-centric model of interpretation couched within the Rational Speech Act framework. Adjective production probabilities a listener expects for objects in a context drive the size of contrastive inferences: the greater the asymmetry in expectation for a speaker to use a pre-nominal adjective for the target rather than for competitors, the greater the listener's resulting target preference. Modifier production probabilities were collected (Exp. 1) and used to make predictions about comprehension in an incremental decision task (Exp. 2). The model's interpretation predictions are supported by the data. This account has the potential to explain the fluctuating appearance of contrastive inferences and shifts the explanatory focus away from contrastive inference towards online interpretation of referring expressions more broadly.

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