Abstract
Music unquestionably affects our emotions. We tend to listen to music that reflects our mood. Music can affect our current emotional state drastically. Earlier, the user used to manually browse songs through the playlist. Over the period, recommendation systems have used collaborative and content-based filtering for creating playlist but not the current emotional state of the user. This paper proposes an idea of an android music player application which recommends songs after determining the user’s emotion by facial recognition at that particular moment using deep learning techniques. And create a playlist by considering the emotion of the user and recommending songs according to the current emotion of the user.
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Sahu, A., Kumar, A., Parekh, A. (2021). Emoticon: Toward the Simulation of Emotion Using Android Music Application. In: Suma, V., Bouhmala, N., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 53. Springer, Singapore. https://doi.org/10.1007/978-981-15-5258-8_62
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DOI: https://doi.org/10.1007/978-981-15-5258-8_62
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