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Prosodic alignment toward emotionally expressive speech: Comparing human and Alexa model talkers

Michelle Cohn,Kristin Predeck,Melina Sarian,Georgia Zellou

Published 2021 in Speech Communication

ABSTRACT

This study tests whether individuals vocally align toward emotionally expressive prosody produced by two types of interlocutors: a human and a voice-activated artificially intelligent (voice-AI) assistant. Participants completed a word shadowing experiment of interjections (e.g., “ Awesome ” ) produced in emotionally neutral and expressive prosodies by both a human voice and a voice generated by a voice-AI system (Amazon ’ s Alexa). Results show increases in participants ’ word duration, mean f0, and f0 variation in response to emotional expressiveness, consistent with increased alignment toward a general ‘positive-emotional ’ speech style. Small differences in emotional alignment by talker category (human vs. voice-AI) parallel the acoustic differences in the model talkers ’ productions, suggesting that participants are mirroring the acoustics they hear. The similar responses to emotion in both a human and voice-AI talker support accounts of unmediated emotional alignment, as well as computer personification: people apply emotionally-mediated behaviors to both types of interlocutors. While there were small differences in magnitude by participant gender, the overall patterns were similar for women and men, supporting a nuanced picture of emotional vocal alignment.

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