Bi-Sampling Approach to Classify Music Mood leveraging Raga-Rasa Association in Indian Classical Music
This addresses the need for intelligent music classifiers and recommenders in cloud applications, but it is incremental as it applies existing machine learning techniques to a specific cultural domain.
The paper tackles the problem of classifying music mood by leveraging raga-rasa associations in Indian classical music, resulting in a framework for building an intelligent classifier and recommendation system based on user mood.
The impact of Music on the mood or emotion of the listener is a well-researched area in human psychology and behavioral science. In Indian classical music, ragas are the melodic structure that defines the various styles and forms of the music. Each raga has been found to evoke a specific emotion in the listener. With the advent of advanced capabilities of audio signal processing and the application of machine learning, the demand for intelligent music classifiers and recommenders has received increased attention, especially in the 'Music as a service' cloud applications. This paper explores a novel framework to leverage the raga-rasa association in Indian classical Music to build an intelligent classifier and its application in music recommendation system based on user's current mood and the mood they aspire to be in.