Prosody and Intention Recognition

Listeners face multiple challenges in mapping prosody onto intentions: The relevant intentions vary with the general context of an utterance (e.g., the speaker’s goals) and how prosodic contours are realized varies across speakers, accents, and speech conditions. We propose that listeners map acoustic information onto prosodic representations using (rational) probabilistic inference, in the form of generative models, which are updated on the fly based on the match between predictions and the input. We review some ongoing work, motivated by this framework, focusing on the “It looks like an X” construction, which, depending on the pitch contour and context, can be interpreted as “It looks like an X and it is” or “It looks like an X and it isn’t.” We use this construction to investigate the hypothesis that pragmatic processing shows the pattern of adaptation effects that is expected if the mapping of speech onto intentions involves rational inference.