Abstract
Music has become an integral part that enriches human lives. It serves as a method of entertainment in social gatherings. Consequently Different playlists of music are played to energize, uplift, and comfort listeners in social gatherings. If most in that group of people don’t like the songs playing energy in between them can be lost. In this study, a musical companion robot was developed to interact with the audience through its rhythmic behaviors and through the song selections done by the robot based on the moods of the audience using Neural Networks and emotion recognition through facial recognition. The study demonstrated high levels of user acceptance based on the feedback received from a sample set of 15 volunteers within the age range of 21–25 years. Though The robot’s interaction through its rhythmic behaviors was a success, the song selection algorithm was below the level of acceptance at the startup of the robot. However, as the data demonstrates, the robot was able to accomplish the task of enhancing the audience through its appearance and behaviors.
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Hansika, W.K.N., Nanayakkara, L.Y., Gammanpila, A., de Silva, R. (2020). AuDimo: A Musical Companion Robot to Switching Audio Tracks by Recognizing the Users Engagement. In: Stephanidis, C., Kurosu, M., Degen, H., Reinerman-Jones, L. (eds) HCI International 2020 - Late Breaking Papers: Multimodality and Intelligence. HCII 2020. Lecture Notes in Computer Science(), vol 12424. Springer, Cham. https://doi.org/10.1007/978-3-030-60117-1_7
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