Abstract
Cochlear implants can successfully restore hearing in profoundly deaf individuals and enable speech comprehension. However, the acoustic signal provided is severely degraded and, as a result, many important acoustic cues for perceiving emotion in voices and music are unavailable. The deficit of cochlear implant users in auditory emotion processing has been clearly established. Yet, the extent to which this deficit and the specific cues that remain available to cochlear implant users are unknown due to several confounding factors.
Here we assessed the recognition of the most basic forms of auditory emotion and aimed to identify which acoustic cues are most relevant to recognize emotions through cochlear implants. To do so, we used stimuli that allowed vocal and musical auditory emotions to be comparatively assessed while controlling for confounding factors. These stimuli were used to evaluate emotion perception in cochlear implant users (Experiment 1) and to investigate emotion perception in natural versus cochlear implant hearing in the same participants with a validated cochlear implant simulation approach (Experiment 2).
Our results showed that vocal and musical fear was not accurately recognized by cochlear implant users. Interestingly, both experiments found that timbral acoustic cues (energy and roughness) correlate with participant ratings for both vocal and musical emotion bursts in the cochlear implant simulation condition. This suggests that specific attention should be given to these cues in the design of cochlear implant processors and rehabilitation protocols (especially energy, and roughness). For instance, music-based interventions focused on timbre could improve emotion perception and regulation, and thus improve social functioning, in children with cochlear implants during development.
•Cochlear implant (CI) processing impairs emotional recognition, particularly fear.•A validated CI-simulation approach is presented alongside CI patient data.•Timbral acoustic cues are important for auditory emotion recognition in CI.