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The number of people who attend virtual meetings has increased as a result of COVID-19. In this paper, we present a system that consists of an expressive humanoid social robot called QTRobot, and a recommender system that employs natural language processing techniques to recommend images related to the content of the presenter’s speech to the audience in real time. This is achieved utilising the QTRobot’s platform capabilities (microphone, computation power, and Wi-Fi).

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This work has been funded by the Luxembourg National Research Fund under Grant No. IS/14717072.

This work is partially supported by the Chist-Era grant CHIST-ERA19-XAI-005, and by (i) the Swiss National Science Foundation (G.A. 20CH21_195530), (ii) the Italian Ministry for Universities and Research, (iii) the Luxembourg National Research Fund (G.A. INTER/CHIST/19/14589586), (iv) the Scientific and Research Council of Turkey (TÜBİTAK, G.A. 120N680).

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Correspondence to Benoît Alcaraz .

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Alcaraz, B., Hosseini-Kivanani, N., Najjar, A. (2022). IRRMA: An Image Recommender Robot Meeting Assistant. In: Dignum, F., Mathieu, P., Corchado, J.M., De La Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection. PAAMS 2022. Lecture Notes in Computer Science(), vol 13616. Springer, Cham.

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