Emotion Based Music Recommendation System Using Wearable Physiological Sensors
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: data acquisition, emotion classification, and musicrecommendation. Wearable sensors continuously
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
2024-06-07
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(06), 1760–1763. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2511
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