Affect-enhancing speech features for robotic communication

Klüber, Kim; Onnasch, Linda

doi:10.1177/1071181322661090

Cited by 1 publication

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“…Hoffmann et al [11] revealed that robot errors do not negatively impact liking, trust and acceptance if a robot uses a warm and human-like language. Furthermore, studies have shown that an appropriate vocal prosody has positive effects in terms of empathy [12] and the perception of social abilities [13]. Focusing on sound and noise as non-verbal communication for HRI, Joosse et al [14] demonstrated that intentional noise instead of constant noise accompanying a robot's approach velocity led to more positive attitudes and was helpful to communicate the robot's goals to the user.…”

Section: Introduction "A Social Robot Cannot Not Communicate" (L Kuno...mentioning

confidence: 99%

A Framework to Study and Design Communication with Social Robots

Kunold

Onnasch

2022

Robotics

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Communication is a central component in social human–robot interaction that needs to be planned and designed prior to the actual communicative act. We therefore propose a pragmatic, linear view of communication design for social robots that corresponds to a sender–receiver perspective. Our framework is based on Lasswell’s 5Ws of mass communication: Who, says what, in which channel, to whom, with what effect. We extend and adapt this model to communication in HRI. In addition, we point out that, besides the predefined communicative acts of a robot, other characteristics, such as a robot’s morphology, can also have an impact on humans, since humans tend to assign meaning to every cue in robots’ behavior and appearance. We illustrate the application of the extended framework to three different studies on human–robot communication to demonstrate the incremental value as it supports a systematic evaluation and the identification of similarities, differences, and research gaps. The framework therefore offers the opportunity for meta-analyses of existing research and additionally draws the path for future robust research designs for studying human–robot communication.

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