Active listening is a well-known skill applied in human communication to build intimacy and elicit self-disclosure to support a wide variety of cooperative tasks. When applied to conversational UIs, active listening from machines can also elicit greater self-disclosure by signaling to the users that they are being heard, which can have positive outcomes. However, it takes considerable engineering effort and training to embed active listening skills in machines at scale, given the need to personalize active-listening cues to individual users and their specific utterances. A more generic solution is needed given the increasing use of conversational agents, especially by the growing number of socially isolated individuals. With this in mind, we developed an Amazon Alexa skill that provides privacy-preserving and pseudo-random backchanneling to indicate active listening. User study (N = 40) data show that backchanneling improves perceived degree of active listening by smart speakers. It also results in more emotional disclosure, with participants using more positive words. Perception of smart speakers as active listeners is positively associated with perceived emotional support. Interview data corroborate the feasibility of using smart speakers to provide emotional support. These findings have important implications for smart speaker interaction design in several domains of cooperative work and social computing.
翻译:积极监听是人类通信中应用的一种众所周知的技能,用于建立亲密关系和进行自我披露,以支持广泛的合作任务。在应用到对话性普遍化时,机器的积极监听也可以通过向用户发出信号,让用户知道他们正在被听到,这会产生积极的结果。然而,鉴于需要将主动倾听的信号与个别用户及其具体言论进行个性化化化,需要大量工程努力和培训,将积极的监听技能纳入规模的机器中,因为需要将积极倾听的信号与个人用户及其具体言论相匹配。鉴于对对话代理人的日益使用,特别是社会上孤立的人越来越多,因此需要一种更通用的解决办法。我们为此开发了亚马逊亚历山大技术,提供隐私保护以及假随机回流,以显示积极的监听。用户研究(N=40)数据显示,后冲式的观念提高了智能演讲者对积极监听程度的认知。参与者使用更积极的言词,对作为积极倾听者的看法与感知的情感支持有着积极的联系。访谈数据证实了使用智能演讲者提供情感支持的可行性。这些发现证实了使用智能演讲者提供情感支持的可行性。这些结论对智能互动设计若干领域具有重要的影响。