English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This chapter provides a perspective from the latest EEG evidence in how brain signals enlighten the neurophysiological and neurocognitive mechanisms underlying the recog‐ nition of socioemotional expression conveyed in human speech and voice, drawing upon event‐related potentials’ studies (ERPs). Human sound can encode emotional mean‐ ings by different vocal parameters in words, real‐ vs. pseudo‐speeches, and vocaliza‐ tions. Based on the ERP findings, recent development of the three‐stage model in vocal processing has highlighted initial‐ and late‐stage processing of vocal emotional stimuli. These processes, depending on which ERP components they were mapped onto, can be divided into the acoustic analysis, relevance and motivational processing, fine‐grained meaning analysis/integration/access, and higher‐level social inference, as the unfolding of the time scale. ERP studies on vocal socioemotions, such as happiness, anger, fear, sadness, neutral, sincerity, confidence, and sarcasm in the human voice and speech have employed different experimental paradigms such as crosssplicing, crossmodality priming, oddball, stroop, etc. Moreover, task demand and listener characteristics affect the neural responses underlying the decoding processes, revealing the role of attention deployment and interpersonal sensitivity in the neural decoding of vocal emotional stimuli. Cultural orientation affects our ability to decode emotional meaning in the voice. Neurophysiological patterns were compared between normal and abnormal emotional processing in the vocal expressions, especially in schizophrenia and in congenital amu‐ sia. Future directions highlight the study on human vocal expression aligning with other nonverbal cues, such as facial and body language, and the need to synchronize listener's brain potentials with other peripheral measures.

Tracking the Sound of Human Affection: EEG Signals Reveal Online Decoding of Socio-Emotional Expression in Human Speech and Voice