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Emotion Based Song Recommendation System

Lalita Moharkar, Yukta Rane, Keval Meher, Ruchika Narad, Mukesh Kurmi

Abstract


Emotions are a way in which human express themselves to communicate, connect and interact with other humans. Emotions are a way to express our current state of mind. There are various ways in which human connect with their emotions be it through meditation, exercise, listening to music or doing something creative like painting or drawing. We can connect with our emotions to enhance them and to feel them. Studies have shown that listening to music has a great effect on our emotions. Because of music we can connect and enhance our emotions. In this paper we have put forth how the process of manually selecting music related to our emotions can be automated

 

Keywords: Emotion recognition, CWT, CNN classification


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References


Lahane, P., & Sangaiah, A. K. (2015). An approach to EEG based emotion recognition and classification using kernel density estimation. Procedia Computer Science, 48, 574-581.

Liu, J., Meng, H., Nandi, A., & Li, M. (2016, August). Emotion detection from EEG recordings. In 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (pp. 1722-1727). IEEE.

Alarcao, S. M., & Fonseca, M. J. (2017). Emotions recognition using EEG signals: A survey. IEEE Transactions on Affective Computing, 10(3), 374-393.

Bazgir, O., Mohammadi, Z., & Habibi, S. A. H. (2018, November). Emotion recognition with machine learning using EEG signals. In 2018 25th National and 3rd International Iranian Conference on Biomedical Engineering (ICBME) (pp. 1-5). IEEE.

Koelstra, S., Muhl, C., Soleymani, M., Lee, J. S., Yazdani, A., Ebrahimi, T., ... & Patras, I. (2011). Deap: A database for emotion analysis; using physiological signals. IEEE transactions on affective computing, 3(1), 18-31.


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