A user study of a humanoid robot as a social mediator for two-person conversations
In this work we have enhanced the perception of a humanoid robot by integrating it with a social state estimation system. We present a user study of the humanoid Nao robot as a social mediator, comprising two sets of experiments. In the first sets of experiments, the participants rate their understa...
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Main Authors: | , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/141981 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | In this work we have enhanced the perception of a humanoid robot by integrating it with a social state estimation system. We present a user study of the humanoid Nao robot as a social mediator, comprising two sets of experiments. In the first sets of experiments, the participants rate their understanding of feedback messages delivered via the Nao robot. They also assess two modalities to deliver the feedback: audio only and audio combined with gestures. In almost all cases there is an improvement of 10% or more when audio and gesture modalities are combined to deliver feedback messages. For the second sets of experiments the sociofeedback system was integrated with the Nao robot. The participants engage in two-person scenario-based conversations while the Nao robot acts as a mediator. The sociofeedback system analyzes the conversations and provides feedback via Nao. Subsequently, the participants assess the received sociofeedback with respect to various aspects, including its content, appropriateness, and timing. Participants also evaluate their overall perception of Nao as social mediator via the Godspeed questionnaire. The results indicate that the social feedback system is able to detect the social scenario with 93.8% accuracy and that Nao can be effectively used to provide sociofeedback in discussions. The results of this paper pave the way to natural human-robot interactions for social mediators in multi-party dialog systems. |
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