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Both appearance and motion are important considerations in designing robots for interaction with humans. In communication, humans sense intelligence in their conversation partner. We aim to develop an intelligent robot that communicates in the same intelligent and human-like way in daily life. We use the Total Turing Test to evaluate the human-likeness of the android. In this test, subjects are shown either the android or another human for a short time. Subjects are then asked whether it was a human being or not. The android used in this study is called ReplieeQ2, which has an appearance and motions that closely resemble those of a human being. We hypothesize that an android that is given more human-like motions will be identified as a human in the Total Turing Test more often. To create human-like motion we observed humans behavior when sitting. We focused on eye, eyelid, neck and chest motions and analyzed them in detail. The android motions were made from this analysis and used in the Total Turing Test. We prepared three conditions: a static android (SA), an android given natural motions (MA), and a human sitting naturally (SH). We expose a subject to one of these conditions for either one or two seconds. We then examine how often they correctly identify the condition as either human or robot. SH was identified as human most often, followed by MA and then SA, for both exposure times.
Noma et al. (Fri,) studied this question.
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