The mess reveals the system: People use top-down cues to resolve errors in contexts with highly random noise, but not with highly structured noise

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Listeners seem to use their grammatical knowledge to correct for noise in speech, but what roles does contextual and statistical information play in determining if and how to correct? To investigate this, we first replicate Mack et al. (2012), a study which investigated usage preferences for null-subject constructions using a speech restoration paradigm. By manipulating the placement of the noise in the fillers, we construct two additional experiments with either random or highly-structured noise distribution. While still ongoing, preliminary results from the study show listeners seem to place less importance on grammaticality-based correction strategies when faced with highly structured noise.

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