Causal inference explains the stimulus-level relationship between the McGurk Effect and auditory speech perception
The McGurk effect is widely used as a measure of multisensory integration during speech perception. Two observations have raised questions about the relationship between the effect and everyday speech perception. First, there is high variability in the strength of the McGurk effect across different stimuli and observers. Second, there is low correlation across observers between perception of the McGurk effect and measures of everyday speech perception, such as the ability to understand noisy audiovisual speech. Using the framework of the causal inference of multisensory speech (CIMS) model, we explored the relationship between the McGurk effect, syllable perception, and sentence perception in seven experiments with a total of 296 different participants. Perceptual reports revealed a relationship between the efficacy of different McGurk stimuli created from the same talker and perception of the auditory component of the McGurk stimuli presented in isolation, either with or without added noise. The CIMS model explained this high stimulus-level correlation using the principles of noisy sensory encoding followed by optimal cue combination within a representational space that was identical for McGurk and everyday speech. In other experiments, CIMS successfully modeled low observer-level correlation between McGurk and everyday speech. Variability in noisy speech perception was modeled using individual differences in noisy sensory encoding, while variability in McGurk perception involved additional differences in causal inference. Participants with all combinations of high and low sensory encoding noise and high and low causal inference disparity thresholds were identified. Perception of the McGurk effect and everyday speech can be explained by a common theoretical framework that includes causal inference.