Alle Publikationen
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2019
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(2019) : Good Robot Design or Machiavellian? An In-the-Wild Robot Leveraging Minimal Knowledge of Passersby’s Culture: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 382-391
DOI: https://doi.org/10.1109/HRI.2019.8673326 Abstract: Social robots are being designed to use human-like communication techniques, including body language, social signals, and empathy, to work effectively with people. Just as between people, some robots learn about people and adapt to them. In this paper we present one such robot design: we developed Sam, a robot that learns minimal information about a person’s background, and adapts to this background. Our in-the-wild study found that people helped Sam for significantly longer when it adapted to match their background. While initially we saw this as a success, in re-considering our study we started seeing a different angle. Our robot effectively deceived people (changed its story and text), based on some knowledge of their background, to get more work from them. There was little direct benefit to the person from this adaptation, yet the robot stood to gain free labor. We would like to pose the question to the community: is this simply good robot design, or, is our robot being manipulative? Where does the ethical line lay between a robot leveraging social techniques to improve interaction, and the more negative framing of a robot or algorithm taking advantage of people? How can we decide what is good here, and what is less desirable?
Keywords: Body language, Cultural differences, Culture, Ethics, Global communication, human-like communication techniques, human-robot interaction, ieee xplore, in the wild, in-the-wild robot, learning (artificial intelligence), minimal information, Mobile robots, Mood, Moral & Ethik, passersby culture, Persuasive Robots, robot design, Robots, Sam, Shape, social robots, Social signals, social techniques, Task Analysis 2014
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(2014) : A system for feature classification of emotions based on speech analysis; applications to human-robot interaction: 2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM): Tehran, Iran: IEEE, S. 795-800
DOI: https://doi.org/10.1109/ICRoM.2014.6991001 Abstract: A system for recognition of emotions based on speech analysis can have interesting applications in human robot interaction. Robot should make a proper mutual communication between sound recognition and perception for creating a desired emotional interaction with humans. Advanced research in this field will be based on sound analysis and recognition of emotions in spontaneous dialog. In this paper, we report the results obtained from an exploratory study on a methodology to automatically recognize and classify basic emotional states. The study attempted to investigate the appropriateness of using acoustic and phonetic properties of emotive speech with the minimal use of signal processing algorithms. The efficiency of the methodology was evaluated by experimental tests on adult European speakers. The speakers had to repeat six simple sentences in English language in order to emphasize features of the pitch (peak, value and range), the intensity of the speech, the formants and the speech rate. The proposed methodology using the freeware program (PRAAT) and consists of generating and analyzing a graph of pitch, formant and intensity of speech signals for classify basic emotion. Eventually, the proposed model provided successful recognition of the basic emotion in most of the cases.
Keywords: acoustic properties, Acoustics, adult European speakers, Angemessen(heit) (von Technik), emotion feature classification, emotion recognition, emotional interaction, emotional state classification, emotional state recognition, emotive speech, English language, Feature extraction, formant, formants, graph analysis, graph generation, graph theory, human-robot interaction, ieee xplore, mutual communication, phonetic properties, pitch, pitch features, PRAAT freeware program, public domain software, Shape, signal classification, signal processing algorithms, sound analysis, sound perception, sound recognition, speech, speech analysis, speech intensity, speech rate, speech recognition, speech signals, spontaneous dialog 2008
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(2008) : Are bigger robots scary? —The relationship between robot size and psychological threat—: 2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics: Xian, China: IEEE, S. 546-551
DOI: https://doi.org/10.1109/AIM.2008.4601719 Abstract: Human symbiosis service robots of various sizes have already been developed. However, few quantitative investigations have been made concerning the influence of the size of a robot on a userpsilas impression. We focused on the height of a robot (robot size), investigating the effect of robot size on the anxiety or threat felt by a human to be caused by a robot and the appropriate human-robot distance. We prepared three mobile robots that were 0.6 m, 1.2 m and 1.8 m tall. One of these robots approached a male subject from a distance of 3 m, at a maximum speed of 0.4 m/s, and the subject stopped the robot using a switch when he began to feel anxious. We measured the distance between the human and the robot when the subject stopped the robot. Then, we asked the subject to complete a questionnaire to evaluate differences in anxiety levels caused by robots of different sizes. As a result of the experiment based on 19 subjects, we were able to observe a tendency for the human-robot distance to increase along with the size of the robot. From the questionnaires, we found that the subjects felt most anxious with the 1.8-m-tall robots, but that some subjects also experienced anxiety with the 0.6-m-tall robots. Considering both the experimental results and the questionnaires, we conclude that 1.2 m is better than other two sizes.
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