Emotion of Music: Extraction and Composing
DOI:
https://doi.org/10.54097/ehss.v13i.8207Keywords:
MER; Emotional composition; Music; Emotion extraction.Abstract
Music, the third art that has accompanied the development of human civilization, has played a vital role in human expression of emotions from ancient times to the present. It has played a vital role in human expression of emotions from ancient times to the present. This study describes three different ways of musical emotional extraction within the current research field: a. Extraction by measuring the physiological characteristics of the subject; b. text feature extraction by analyzing lyrics in songs and c. extraction by analyzing audio features. This paper also discusses the research results of three different groups of researchers to use specific emotions for music creation by designing and applying the GA based on KTH rule system, the mLSMN with logistic regression, and the MAgentM framework. The purpose of this research is to provide reference materials for subsequent researchers through the detailed introduction of the MER method, and to provide industry stakeholders with an outlook for the music industry.
Downloads
References
Perlovsky L. Musical emotions: Functions, origins, evolution. Physics of life reviews, 2010, 7(1): 2-27.
De Berardinis J, Cangelosi A, Coutinho E. The multiple voices of musical emotions: Source separation for improving music emotion recognition models and their interpretability. Proceedings of the 21st international society for music information retrieval conference. 2020: 310-317.
Liu J, Huang M. Music emotion understanding by computer based on BP neural network. 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2017: 1-5.
Kim Y E, Schmidt E M, Migneco R, et al. Music emotion recognition: A state of the art review. Proc. ismir. 2010, 86: 937-952.
Russell J A. A circumplex model of affect. Journal of personality and social psychology, 1980, 39(6): 1161.
Juslin P N. What does music express? Basic emotions and beyond. Frontiers in psychology, 2013, 4: 596.
Juslin P N, Laukka P. Expression, perception, and induction of musical emotions: A review and a questionnaire study of everyday listening. Journal of new music research, 2004, 33(3): 217-238.
Hsu Y L, Wang J S, Chiang W C, et al. Automatic ECG-based emotion recognition in music listening. IEEE Transactions on Affective Computing, 2017, 11(1): 85-99.
Chen S H, Lee Y S, Hsieh W C, et al. Music emotion recognition using deep Gaussian process. 2015 Asia-Pacific signal and information processing association annual summit and conference (APSIPA). IEEE, 2015: 495-498.
Jamdar A, Abraham J, Khanna K, et al. Emotion analysis of songs based on lyrical and audio features. arXiv preprint arXiv:1506.05012, 2015.
Liu C H, Ting C K. Computational intelligence in music composition: A survey. IEEE Transactions on Emerging Topics in Computational Intelligence, 2016, 1(1): 2-15.
Ferreira L N, Whitehead J. Learning to generate music with sentiment. arXiv preprint arXiv:2103.06125, 2021.
Casella P, Paiva A. Magenta: An architecture for real time automatic composition of background music. Intelligent Virtual Agents: Third International Workshop, IVA 2001 Madrid, Spain, September 10–11, 2001 Proceedings 3. Springer Berlin Heidelberg, 2001: 224-232.
Yang X, Dong Y, Li J. Review of data features-based music emotion recognition methods. Multimedia systems, 2018, 24: 365-389.
Xu J, Li X, Hao Y, et al. Source separation improves music emotion recognition. Proceedings of international conference on multimedia retrieval. 2014: 423-426.
Downloads
Published
Issue
Section
License

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






