Emotion Based Music Recommendation System Using Wearable Physiological Sensors

Authors

  • Dr.A.Nagarjuna Reddy,Mandadi Harshitha, Gonuguntla Tejaswini, Thatikonda Bhuvaneshwari

Keywords:

Emotion Analysis, Music Recommendation, Feature Extraction, Machine Learning Models, User Interaction, Genre Classification, Data Sources, Context Awareness, NLP, Evaluation Metrics.

Abstract

This study introduces an innovative Emotion-Based Music Recommendation System (EBMRS) thatutilizes real-time physiological data from wearable sensors to personalize music playlists based on the user'semotional state. The system comprises three key components:

References

. Anagha S.Dhavalikar and Dr. R. K. Kulkarni, “Face Detection and Facial Expression Recognition System” 2014 Interntional Conference on Electronics and Communication System (ICECS -2014).

. Yong-Hwan Lee , Woori Han and Youngseop Kim, “Emotional Recognition from Facial Expression Analysis using Bezier Curve Fitting”

16th International Conference on Network- Based Information Systems.

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Published

2024-04-16

How to Cite

Dr.A.Nagarjuna Reddy,Mandadi Harshitha, Gonuguntla Tejaswini, Thatikonda Bhuvaneshwari. (2024). Emotion Based Music Recommendation System Using Wearable Physiological Sensors. Journal of Computational Analysis and Applications (JoCAAA), 33(4), 760–763. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2467

Issue

Vol. 33 No. 4 (2024): Selected Papers on Computational Techniques Across Multidisciplinary Fields: Innovations and Applications

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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