The Impact of Personalisation on Human-Robot Interaction in Learning Scenarios
| Autor: | Hwei Geok Ng, Johannes Twiefel, Thi Linh Chi Nguyen, Cornelius Weber, Julius Mayer, Nicolás Navarro-Guerrero, Nikhil Churamani, Marc Brugger, Marcus Soll, Waleed Mustafa, Thomas Hummel, Quan Nguyen, Erik Strahl, Paul Anton, Sebastian Springenberg, Sascha Griffiths, Erik Fließwasser, Stefan Wermter, Stefan Heinrich |
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| Rok vydání: | 2017 |
| Předmět: |
Social robot
Multimedia Computer science media_common.quotation_subject Natural language understanding 02 engineering and technology computer.software_genre Human–robot interaction Personalization 030507 speech-language pathology & audiology 03 medical and health sciences 0202 electrical engineering electronic engineering information engineering Natural (music) Robot 020201 artificial intelligence & image processing Conversation 0305 other medical science computer Natural language media_common |
| Zdroj: | HAI |
| DOI: | 10.1145/3125739.3125756 |
| Popis: | Advancements in Human-Robot Interaction involve robots being more responsive and adaptive to the human user they are interacting with. For example, robots model a personalised dialogue with humans, adapting the conversation to accommodate the user's preferences in order to allow natural interactions. This study investigates the impact of such personalised interaction capabilities of a human companion robot on its social acceptance, perceived intelligence and likeability in a human-robot interaction scenario. In order to measure this impact, the study makes use of an object learning scenario where the user teaches different objects to the robot using natural language. An interaction module is built on top of the learning scenario which engages the user in a personalised conversation before teaching the robot to recognise different objects. The two systems, i.e. with and without the interaction module, are compared with respect to how different users rate the robot on its intelligence and sociability. Although the system equipped with personalised interaction capabilities is rated lower on social acceptance, it is perceived as more intelligent and likeable by the users. |
| Databáze: | OpenAIRE |
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