Exploring the Interplay Between Voice, Personality, and Gender in Human-Agent Interactions

TL;DR

This study investigates how agent gender and voice-derived personality cues shape user perceptions in voice-only human-agent interactions. Using four synthesized voices generated from pre-sample extroversion-extrovert cues, the authors test whether users can discern personality and whether user personality synchrony affects judgments, employing nonparametric analyses on 388 participants. Key findings show female agent voices reliably convey personality distinctions, while male voices do not, and that users tend to project their own personality onto the first voice heard, particularly among male participants. The results highlight the nuanced role of gender and early interaction cues in shaping trust and engagement with virtual agents, offering design implications for context-aware voice design and synchrony management in HCI. practical impact lies in informing voice design strategies to optimize credibility and rapport in human-agent workflows, especially in domains like education and mental health support.

Abstract

To foster effective human-agent interactions, designers need to identify characteristics that could affect how agents are perceived and accepted, and to what extent they could impact rapport-building. Aiming to explore the role of user-agent synchrony, we assessed 388 participants to determine whether they could perceive personality traits from four artificial voices we selected and adapted from human samples, considering gender (male or female) and personality (introvert or extrovert) as grouping factors. Our findings suggest that participants were able to significantly differentiate female agents by personality, while male agents were not consistently distinguished. We also observed evidence of personality synchrony, where participants tended to perceive the first agent as more similar to their own personality, with this effect driven mainly by male participants, especially toward male agents. This paper contributes findings and insights to consider the interplay of user-agent personality and gender synchrony in the design of human-agent interactions.

Figures (3)

• Figure 1: Sample Population and Participant Grouping
• Figure 2: Extroversion Score Distribution (TIPI GOSLING2003504) for Users’ First Interaction with a Female Voice
• Figure 3: Extroversion Score Distribution (TIPI GOSLING2003504) for Users’ First Interaction with a Male Voice