Abstract
Emotions can be challenging to describe and interpret, which is why music has been proposed as an art. In recent times, music can be used as a mood regulation mode, to assist someone balance, understand and deal with their emotions better. ‘Euphonia’ is intended at easing that process. The purpose of ‘Euphonia’ is to use real-time facial recognition to acquaint the machine with abilities to recognize and examine human emotions. With this, the machine will be trained to provide the user with suitable songs for that particular mood. Besides this, the machine will also recommend the user with a general playlist pertaining to the user’s likes and dislikes which they can access whenever they wish to. Machine learning concepts and the available datasets have been utilized to classify a vast set of music that is stored using automatic music content analyses. It was implemented using Python, Pandas, OpenCV, and NumPy.
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Ramalakshmi, E., Hussain, H., Agarwal, K. (2023). Euphonia: Music Recommendation System Based on Facial Recognition and Emotion Detection. In: Balas, V.E., Semwal, V.B., Khandare, A. (eds) Intelligent Computing and Networking. Lecture Notes in Networks and Systems, vol 632. Springer, Singapore. https://doi.org/10.1007/978-981-99-0071-8_8
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DOI: https://doi.org/10.1007/978-981-99-0071-8_8
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