Weak observer-level correlation and strong stimulus-level correlation between the McGurk effect and audiovisual speech-in-noise: A causal inference explanation.

The McGurk effect is a widely used measure of multisensory integration during speech perception. Two observations have raised questions about the validity of the effect as a tool for understanding speech perception. First, there is high variability in perception of the McGurk effect across different stimuli and observers. Second, across observers there is low correlation between McGurk susceptibility and recognition of visual speech paired with auditory speech-in-noise, another common measure of multisensory integration. 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, both with and without added noise. The CIMS model explained this strong stimulus-level correlation using the principles of noisy sensory encoding followed by optimal cue combination within a common representational space across speech types. Because the McGurk effect (but not speech-in-noise) requires the resolution of conflicting cues between modalities, there is an additional source of individual variability that can explain the weak observer-level correlation between McGurk and noisy speech. Power calculations show that detecting this weak correlation requires studies with many more participants than those conducted to-date. Perception of the McGurk effect and other types of speech can be explained by a common theoretical framework that includes causal inference, suggesting that the McGurk effect is a valid and useful experimental tool.