TY - GEN
T1 - Towards Understanding the Effect of Voice on Human-Agent Negotiation
AU - Mania, Joanna
AU - Miedema, Fieke
AU - Browne, Rose
AU - Broekens, Joost
AU - Oertel, Catharine
PY - 2020
Y1 - 2020
N2 - Virtual agents are increasingly being used for communication training such as public speaking-, job interviews-, as well as negotiation training. In these use-cases the agent is generally taking on the role of interviewer and its behaviour is altered according to the nonverbal cues of its human interlocutor. However, understanding how the agent's non-verbal cues influence human behaviour, perception or interactions outcomes is equally important. This contributes to appropriate behaviour generation in agents, but also to our understanding of the intricate interplay of non-verbal behaviours on human perception and interaction outcomes. This study focuses specifically on the perception of vocal dominance in human-agent negotiation. Earlier research showed that the perception of dominance influences decision making in the course of negotiations, as do concessions tactics. However, the effect of voice as well as the effect of the negotiator type in this regard have been so far under-explored. To close this gap, an online experiment was conducted, in which a total number of 121 participants negotiated with conversational agents displaying either low or high vocal dominance, and an individualistic or neutral concession tactic. The results showed that when taking into account the self-reported type of negotiator, significant differences caused by vocal dominance were evident in regard to the number of negotiation rounds and perceived fairness. The number of rounds was significantly higher for the competitive participant type negotiating with the low vocal dominance agent, and the perceived fairness was significantly lower with the collaborative participant type negotiating with the high vocal dominance agent.
AB - Virtual agents are increasingly being used for communication training such as public speaking-, job interviews-, as well as negotiation training. In these use-cases the agent is generally taking on the role of interviewer and its behaviour is altered according to the nonverbal cues of its human interlocutor. However, understanding how the agent's non-verbal cues influence human behaviour, perception or interactions outcomes is equally important. This contributes to appropriate behaviour generation in agents, but also to our understanding of the intricate interplay of non-verbal behaviours on human perception and interaction outcomes. This study focuses specifically on the perception of vocal dominance in human-agent negotiation. Earlier research showed that the perception of dominance influences decision making in the course of negotiations, as do concessions tactics. However, the effect of voice as well as the effect of the negotiator type in this regard have been so far under-explored. To close this gap, an online experiment was conducted, in which a total number of 121 participants negotiated with conversational agents displaying either low or high vocal dominance, and an individualistic or neutral concession tactic. The results showed that when taking into account the self-reported type of negotiator, significant differences caused by vocal dominance were evident in regard to the number of negotiation rounds and perceived fairness. The number of rounds was significantly higher for the competitive participant type negotiating with the low vocal dominance agent, and the perceived fairness was significantly lower with the collaborative participant type negotiating with the high vocal dominance agent.
KW - Concession Tactic
KW - Negotiation
KW - Virtual Agents
KW - Vocal Dominance
UR - http://www.scopus.com/inward/record.url?scp=85096963478&partnerID=8YFLogxK
U2 - 10.1145/3383652.3423896
DO - 10.1145/3383652.3423896
M3 - Conference contribution
AN - SCOPUS:85096963478
T3 - Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents, IVA 2020
BT - Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents, IVA 2020
PB - Association for Computing Machinery (ACM)
T2 - 20th ACM International Conference on Intelligent Virtual Agents, IVA 2020
Y2 - 20 October 2020 through 22 October 2020
ER -