Vocal Similarity, Trust and Persuasion in Human-Ai Agent Interactions

This research explores an important component that exists in human-AI agent interactions and user personalization – acoustic similarity. We quantify the distance measure as a measure of objective vocal similarity in pitch and timbre (MFCCs) and we show that acoustic similarity leads to higher trust, and perceptions of warmth and competence.


Michael Lowe and Na Kyong Hyun (2020) ,"Vocal Similarity, Trust and Persuasion in Human-Ai Agent Interactions", in NA - Advances in Consumer Research Volume 48, eds. Jennifer Argo, Tina M. Lowrey, and Hope Jensen Schau, Duluth, MN : Association for Consumer Research, Pages: 907-912.


Michael Lowe, Georgia Tech, USA
Na Kyong Hyun, Georgia Tech, USA


NA - Advances in Consumer Research Volume 48 | 2020

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