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Classifying Songs to Relieve Stress Using Machine Learning Algorithms

  • Khongorzul Munkhbat
  • Keun Ho RyuEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 157)

Abstract

Music has a great impact on stress relieving for human. We have become very stressed by society and the times. Accumulated stress cannot be met daily, and this will have an adverse effect on our health and our mental health, such as obesity, heart attacks, insomnia, and so on. Therefore, this study has been offering an ensemble approach combining algorithms of machine learning such as K-NN, naïve Bayes, multilayer perceptron, and random forest for stress relief based on musical genres.

Keywords

Music genre classification Relieving stress songs Machine learning Ensemble approach Classification algorithms 

Notes

Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. 2017R1A2B4010826).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Database/Bioinformatics Laboratoty, School of Electrical and Computer EngineeringChungbuk National UniversityCheongjuSouth Korea
  2. 2.Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam
  3. 3.Department of Computer ScienceCollege of Electrical and Computer Engineering, Chungbuk National UniversityCheongjuSouth Korea

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