Neurophysiological Indices of Audiovisual Speech Processing Reveal a Hierarchy of Multisensory Integration Effects.

Seeing a speaker's face benefits speech comprehension, especially in challenging listening conditions. This perceptual benefit is thought to stem from the neural integration of visual and auditory speech at multiple stages of processing, whereby movement of a speaker's face provides temporal cues to auditory cortex, and articulatory information from the speaker's mouth can aid recognizing specific linguistic units (e.g., phonemes, syllables). However, it remains unclear how the integration of these cues varies as a function of listening conditions. Here, we sought to provide insight on these questions by examining EEG responses in humans (males and females) to natural audiovisual (AV), audio, and visual speech in quiet and in noise. We represented our speech stimuli in terms of their spectrograms and their phonetic features and then quantified the strength of the encoding of those features in the EEG using canonical correlation analysis (CCA). The encoding of both spectrotemporal and phonetic features was shown to be more robust in AV speech responses than what would have been expected from the summation of the audio and visual speech responses, suggesting that multisensory integration occurs at both spectrotemporal and phonetic stages of speech processing. We also found evidence to suggest that the integration effects may change with listening conditions; however, this was an exploratory analysis and future work will be required to examine this effect using a within-subject design. These findings demonstrate that integration of audio and visual speech occurs at multiple stages along the speech processing hierarchy.SIGNIFICANCE STATEMENT During conversation, visual cues impact our perception of speech. Integration of auditory and visual speech is thought to occur at multiple stages of speech processing and vary flexibly depending on the listening conditions. Here, we examine audiovisual (AV) integration at two stages of speech processing using the speech spectrogram and a phonetic representation, and test how AV integration adapts to degraded listening conditions. We find significant integration at both of these stages regardless of listening conditions. These findings reveal neural indices of multisensory interactions at different stages of processing and provide support for the multistage integration framework.

Neural representation of linguistic feature hierarchy reflects second-language proficiency.

Acquiring a new language requires individuals to simultaneously and gradually learn linguistic attributes on multiple levels. Here, we investigated how this learning process changes the neural encoding of natural speech by assessing the encoding of the linguistic feature hierarchy in second-language listeners. Electroencephalography (EEG) signals were recorded from native Mandarin speakers with varied English proficiency and from native English speakers while they listened to audio-stories in English. We measured the temporal response functions (TRFs) for acoustic, phonemic, phonotactic, and semantic features in individual participants and found a main effect of proficiency on linguistic encoding. This effect of second-language proficiency was particularly prominent on the neural encoding of phonemes, showing stronger encoding of "new" phonemic contrasts (i.e., English contrasts that do not exist in Mandarin) with increasing proficiency. Overall, we found that the nonnative listeners with higher proficiency levels had a linguistic feature representation more similar to that of native listeners, which enabled the accurate decoding of language proficiency. This result advances our understanding of the cortical processing of linguistic information in second-language learners and provides an objective measure of language proficiency.