Does computer-generated speech manifest personality? an experimental test of similarity-attraction

  • Authors:
  • Clifford Nass;Kwan Min Lee

  • Affiliations:
  • Department of Communication, Stanford University, Stanford, CA;Department of Communication, Stanford University, Stanford, CA

  • Venue:
  • Proceedings of the SIGCHI conference on Human Factors in Computing Systems
  • Year:
  • 2000

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Abstract

This study examines whether people would interpret and respond to paralinguistic personality cues in computer-generated speech in the same way as they do human speech. Participants used a book-buying website and heard five book reviews in a 2 (synthesized voice personality: extrovert vs. introvert) by 2 (participant personality: extrovert vs. introvert) balanced, between-subjects experiment. Participants accurately recognized personality cues in TTS and showed strong similarity-attraction effects. Although the content was the same for all participants, when the personality of the computer voice matched their own personality: 1) participants regarded the computer voice as more attractive, credible, and informative; 2) the book review was evaluated more positively; 3) the reviewer was more attractive and credible; and 4) participants were more likely to buy the book. Match of user voice characteristics with TTS had no effect, confirming the social nature of the interaction. We discuss implications for HCI theory and design.