Recognition of affective prosody: Continuous wavelet measures of event-related brain potentials to emotional exclamations

The affective state of a speaker can be identified from the prosody of his or her speech. Voice quality is the most important prosodic cue for emotion recognition from short verbal utterances and nonverbal exclamations, the latter conveying pure emotion, void of all semantic meaning. We adopted two context violation paradigms-oddball and priming-to study the event-related brain potentials (ERP) reflecting this recognition process. We found a negative wave, the N300, in the ERPs to contextually incongruous exclamations, and interpreted this component as analogous to the well-known N400 response to semantically inappropriate words. The N300 appears to be a real-time psychophysiological measure of spontaneous emotion recognition from vocal cues, which could prove a useful tool for the examination of affective-prosody comprehension. In addition, we developed a new ERP component detection and estimation method that is based on the continuous wavelet transform (CWT), does not rely on visual inspection of the waveforms, and yields larger statistical difference effects than classical methods.