Publication Type : Conference Proceedings
Publisher : 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)
Source : 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), p.1111-1115 (2020)
Url : https://ieeexplore.ieee.org/document/9074249
Campus : Coimbatore
School : School of Engineering
Department : Electrical and Electronics
Year : 2020
Abstract : Music, as all other art forms, has been used primarily as a vehicle for conveying ideas, experiences and emotions in a stylistic manner. It thus makes sense to attempt to categorize a library of music into either its style or the emotions expressed in the tracks. In this work, preliminary results of the signal processing module and machine learning module with four songs in detail and with a database of 100 songs is carried out. The signal processing algorithms employed are Mel Frequency Cepstral Coefficients and beat Histogram. Human emotions were classified based on Thayers model into Happy, Sad, Angry and Relaxed. The Machine Learning classification algorithms employed are Decision Tree Classifier and Random Forest Classifier. A low accuracy suggests improvement in the features and better machine learning algorithm before porting to Android for development as a Mobile App.
Cite this Research Publication : Supriya P., R. Jayabarathi, C. Jeyanth, Yogeshwar B., Adith Sarvesh, and Mohamed Shurfudeen, “Preliminary Investigation for Tamil cine music deployment for mood music recommender system”, 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). pp. 1111-1115, 2020.