Abstract
Typical Augmented Reality (AR) cultural heritage (CH) guides adopt a visuo-centric approach, wherein visual virtual elements are superimposed onto the physical world. Recent research has investigated the use of Audio AR to evoke multisensory immersive experiences to visitors of CH sites adopting screen-free interfaces to ensure that user attention is not distracted from the physical exhibits. A parallel trend in the audience engagement programs of cultural institutions involves the employment of AI chatbots which are engaged in dialogues with visitors to provide meaningful responses to user questions. Herein, we present Exhibot, an intelligent audio guide system aiming at enhancing the user experience of CH site visitors. Exhibot represents the first-ever approach to combine Audio AR and chatbot technologies to enable natural visitor-exhibit interaction, while also leveraging IoT devices to contextualize the delivered information. The usability and utility of Exhibot has been tested in a case study in outdoors environment with the preliminary results indicating a very positive user experience.
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Notes
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An intent is a collection of user statements carrying the same meaning. For instance, the questions “How old are you?” and “When have you been born?” are classified under the same intent.
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Exhibot demonstration: https://youtu.be/alW3RU41aZo.
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Acknowledgement
This research was funded by the Research e-Infrastructure “Interregional Digital Transformation for Culture and Tourism in Aegean Archipelagos” {Code Number MIS 5047046} which is implemented within the framework of the “Regional Excellence” Action of the Operational Program “Competitiveness, Entrepreneurship and Innovation”. The action was co-funded by the European Regional Development Fund (ERDF) and the Greek State [Partnership Agreement 2014–2020].
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Tsepapadakis, M., Gavalas, D., Koutsabasis, P. (2022). 3D Audio + Augmented Reality + AI Chatbots + IoT: An Immersive Conversational Cultural Guide. In: De Paolis, L.T., Arpaia, P., Sacco, M. (eds) Extended Reality. XR Salento 2022. Lecture Notes in Computer Science, vol 13445. Springer, Cham. https://doi.org/10.1007/978-3-031-15546-8_22
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