Who Is Responsible for a Dialogue Breakdown? An Error Recovery Strategy That Promotes Cooperative Intentions From Humans by Mutual Attribution of Responsibility in Human-Robot Dialogues.
Who Is Responsible for a Dialogue Breakdown? An Error Recovery Strategy That Promotes Cooperative Intentions From Humans by Mutual Attribution of Responsibility in Human-Robot Dialogues.
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DOI：
10.3389/frobt.2019.00029
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发表时间：
2019
影响因子：
3.4
通讯作者：
Ishiguro H
中科院分区：
文献类型：
--
作者：
Uchida T;Minato T;Koyama T;Ishiguro H
我们提出了一种策略，对话机器人可以处理对话故障。为了实现顺畅的人机对话，我们不仅要提高机器人的对话能力，而且要从用户那里获得合作意图，以避免对话失败并从中恢复。如果用户认识到自己对故障负有责任，则可以鼓励合作意向。然而，如果机器人总是责怪用户，他们很快就会变得不那么合作，失去继续讨论的动力。本文假设，顺利的对话，机器人和用户必须分担责任的基础上心理互惠。换句话说，机器人应该交替地将责任归咎于自己和用户。我们提出了一个对话策略，从对话故障的基础上的假设和实验验证了它与一个机器人。实验结果表明，所提出的方法使参与者意识到他们的份额的对话故障的责任，而不减少他们的动机，即使对话故障的数量并没有统计减少与控制条件。这表明，所提出的方法有效地引起了合作意向，从用户在对话。
We propose a strategy with which conversational android robots can handle dialogue breakdowns. For smooth human-robot conversations, we must not only improve a robot's dialogue capability but also elicit cooperative intentions from users for avoiding and recovering from dialogue breakdowns. A cooperative intention can be encouraged if users recognize their own responsibility for breakdowns. If the robot always blames users, however, they will quickly become less cooperative and lose their motivation to continue a discussion. This paper hypothesizes that for smooth dialogues, the robot and the users must share the responsibility based on psychological reciprocity. In other words, the robot should alternately attribute the responsibility to itself and to the users. We proposed a dialogue strategy for recovering from dialogue breakdowns based on the hypothesis and experimentally verified it with an android. The experimental result shows that the proposed method made the participants aware of their share of the responsibility of the dialogue breakdowns without reducing their motivation, even though the number of dialogue breakdowns was not statistically reduced compared with a control condition. This suggests that the proposed method effectively elicited cooperative intentions from users during dialogues.
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