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ArtsIT, Interactivity and Game Creation. Creative Heritage. New Perspectives from Media Arts and Artificial Intelligence. 10th EAI International Conference, ArtsIT 2021, Virtual Event, December 2-3, 2021, Proceedings

Research Article

Questions and Answers: Important Steps to Let AI Chatbots Answer Questions in the Museum

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  • @INPROCEEDINGS{10.1007/978-3-030-95531-1_24,
        author={Stefan Schaffer and Aaron Ru\`{a} and Mino Lee Sasse and Louise Schubotz and Oliver Gustke},
        title={Questions and Answers: Important Steps to Let AI Chatbots Answer Questions in the Museum},
        proceedings={ArtsIT, Interactivity and Game Creation. Creative Heritage. New Perspectives from Media Arts and Artificial Intelligence. 10th EAI International Conference, ArtsIT 2021, Virtual Event, December 2-3, 2021, Proceedings},
        proceedings_a={ARTSIT},
        year={2022},
        month={2},
        keywords={Chatbot Conversational interaction Digital Museum Guide},
        doi={10.1007/978-3-030-95531-1_24}
    }
    
  • Stefan Schaffer
    Aaron Ruß
    Mino Lee Sasse
    Louise Schubotz
    Oliver Gustke
    Year: 2022
    Questions and Answers: Important Steps to Let AI Chatbots Answer Questions in the Museum
    ARTSIT
    Springer
    DOI: 10.1007/978-3-030-95531-1_24
Stefan Schaffer,*, Aaron Ruß, Mino Lee Sasse, Louise Schubotz, Oliver Gustke
    *Contact email: stefan.schaffer@dfki.de

    Abstract

    In this paper, we describe our work within the research project “CHIM - Chatbot in the Museum”. CHIM is an AI-based chatbot prototype that enables conversational interaction using text and speech input: visitors can ask questions about certain artworks and receive answers in multimodal formats (text, audio, image, video). The application will be tested in the Städel Museum, Frankfurt/Main, Germany. To develop a proper Natural Language Understanding module, we adapted an existing categorization approach, gathered visitor questions, and structured them into twelve distinct content types. The preliminary results suggest that our approach to subdivide the previously overloaded content typemeaninginto further categories was successful, leading to a more balanced distribution of the data. We further describe the Natural Language Processing mechanisms employed here; these follow a multi-tiered approach using techniques like Rasa, BERT, and cosine-similarity to generate answers with different degrees of effort. Future steps are the implementation of dialog management, the refinement of the NLP strategies by integrating additional answers for selected exhibits, and the implementation of the final layout and interaction design. We are planning to test and evaluate the CHIM prototype on site in the Städel Museum in late 2021.

    Keywords
    Chatbot Conversational interaction Digital Museum Guide
    Published
    2022-02-10
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-030-95531-1_24
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