ArticleBehavioral sciences (Basel, Switzerland)2026
An Electrophysiological Study on the Neural Responses of Speaker Discrimination.
Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The ability to distinguish speakers based on speech signals is a fundamental human ability essential for social communication, yet the neural mechanisms underlying this process remain poorly understood. The present study investigated the temporal dynamics of neural activity during speaker discrimination using event-related potentials (ERPs). Twenty-four native Mandarin speakers completed two tasks: an oddball session, in which participants passively listened to speech stimuli from standard and deviant speakers, and a voice line-up session, in which participants explicitly judged whether two consecutively presented speech stimuli were produced by the same or different speakers. In the oddball session, deviant stimuli elicited robust mismatch negativity (MMN) and P3a components compared to standard stimuli, indicating pre-attentive detection of speaker changes. In the voice line-up session, the different-speaker condition elicited more negative N1 and N400 amplitudes and more positive P2 amplitudes than the same-speaker condition, suggesting that speaker discrimination engages both early sensory processing and later cognitive integration. No significant differences were observed between the P300 and P600 components. These findings reveal distinct neural signatures associated with speaker-related processing across multiple temporal stages, with the MMN and P3a reflecting automatic detection of speaker-related acoustic changes, and the N1, P2, and N400 reflecting explicit speaker discrimination processes. While the present paradigm cannot fully isolate identity-level representations from low-level acoustic discrimination, the results provide novel ERP evidence on the temporal architecture engaged when listeners process speaker-specific information, contributing to a deeper understanding of speaker-related processing in the broader context of speaker identification research.
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