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Description: Abstract: Human behavior is often remarkable flexible, showing the ability to quickly adapt to the statistical peculiarities of a particular local context. When it comes to language, previous work has shown that listeners' anticipatory interpretations of intonational cues are adapted dynamically when cues are observed to be stochastically unreliable. This paper reports novel empirical data from manual response dynamics (mouse-tracking) on how listeners adapt their predictive interpretation of intonational cues when some cues are occasionally unreliable while others are consistently reliable. A Bayesian model of rational belief dynamics predicts that listeners should adapt differently to different unreliable intonational cues, as a function of their initial evidential value. These predictions are borne out by our data.