Neural dynamics of audiovisual speech integration under variable listening conditions: an individual participant analysis

Generalizable EEG Encoding Models with Naturalistic Audiovisual Stimuli

In natural conversations, listeners must attend to what others are saying while ignoring extraneous background sounds. Recent studies have used encoding models to predict electroencephalography (EEG) responses to speech in noise-free listening situations, sometimes referred to as "speech tracking." Researchers have analyzed how speech tracking changes with different types of background noise. It is unclear, however, whether neural responses from acoustically rich, naturalistic environments with and without background noise can be generalized to more controlled stimuli. If encoding models for acoustically rich, naturalistic stimuli are generalizable to other tasks, this could aid in data collection from populations of individuals who may not tolerate listening to more controlled and less engaging stimuli for long periods of time. We recorded noninvasive scalp EEG while 17 human participants (8 male/9 female) listened to speech without noise and audiovisual speech stimuli containing overlapping speakers and background sounds. We fit multivariate temporal receptive field encoding models to predict EEG responses to pitch, the acoustic envelope, phonological features, and visual cues in both stimulus conditions. Our results suggested that neural responses to naturalistic stimuli were generalizable to more controlled datasets. EEG responses to speech in isolation were predicted accurately using phonological features alone, while responses to speech in a rich acoustic background were more accurate when including both phonological and acoustic features. Our findings suggest that naturalistic audiovisual stimuli can be used to measure receptive fields that are comparable and generalizable to more controlled audio-only stimuli.SIGNIFICANCE STATEMENT Understanding spoken language in natural environments requires listeners to parse acoustic and linguistic information in the presence of other distracting stimuli. However, most studies of auditory processing rely on highly controlled stimuli with no background noise, or with background noise inserted at specific times. Here, we compare models where EEG data are predicted based on a combination of acoustic, phonetic, and visual features in highly disparate stimuli-sentences from a speech corpus and speech embedded within movie trailers. We show that modeling neural responses to highly noisy, audiovisual movies can uncover tuning for acoustic and phonetic information that generalizes to simpler stimuli typically used in sensory neuroscience experiments.

Normative data on audiovisual speech integration using sentence recognition and capacity measures

OBJECTIVE

The ability to use visual speech cues and integrate them with auditory information is important, especially in noisy environments and for hearing-impaired (HI) listeners. Providing data on measures of integration skills that encompass accuracy and processing speed will benefit researchers and clinicians.

DESIGN

The study consisted of two experiments: First, accuracy scores were obtained using City University of New York (CUNY) sentences, and capacity measures that assessed reaction-time distributions were obtained from a monosyllabic word recognition task.

STUDY SAMPLE

We report data on two measures of integration obtained from a sample comprised of 86 young and middle-age adult listeners:

RESULTS

To summarize our results, capacity showed a positive correlation with accuracy measures of audiovisual benefit obtained from sentence recognition. More relevant, factor analysis indicated that a single-factor model captured audiovisual speech integration better than models containing more factors. Capacity exhibited strong loadings on the factor, while the accuracy-based measures from sentence recognition exhibited weaker loadings.

CONCLUSIONS

Results suggest that a listener's integration skills may be assessed optimally using a measure that incorporates both processing speed and accuracy.

Hearing impairment and audiovisual speech integration ability: a case study report

Research in audiovisual speech perception has demonstrated that sensory factors such as auditory and visual acuity are associated with a listener's ability to extract and combine auditory and visual speech cues. This case study report examined audiovisual integration using a newly developed measure of capacity in a sample of hearing-impaired listeners. Capacity assessments are unique because they examine the contribution of reaction-time (RT) as well as accuracy to determine the extent to which a listener efficiently combines auditory and visual speech cues relative to independent race model predictions. Multisensory speech integration ability was examined in two experiments: an open-set sentence recognition and a closed set speeded-word recognition study that measured capacity. Most germane to our approach, capacity illustrated speed-accuracy tradeoffs that may be predicted by audiometric configuration. Results revealed that some listeners benefit from increased accuracy, but fail to benefit in terms of speed on audiovisual relative to unisensory trials. Conversely, other listeners may not benefit in the accuracy domain but instead show an audiovisual processing time benefit.