Home About Login Current Archives Announcements Editorial Board
Submit Now For Authors Call for Submissions Statistics Contact
Home > Archives > Volume 20, No 11 (2022) > Article

DOI: 10.14704/nq.2022.20.11.NQ66083

Indian raga identification using machine learning for music therapy

Anitha K,Dr. Parameshachari B D,


In India, the idea of music therapy is discussed using a variety of terminology, including raga therapy, nada chiquita, nada yoga, and raga chiquita. Music is the one universal language among the numerous spoken and written languages used to communicate information. Music has the power to affect anyone. Listening to music is enjoyable, and it also serves as a therapeutic tool for many mental diseases. With the aid of contemporary science, the therapeutic benefits of music have been found in modern medicine. Patients Treatment using therapy of music with physical and mental health issues has gained importance recently.Algorithms based on Machine learning are used to identify the Raga’s Performance, the accuracy of the system comparing saturation using pitch, and the System used to identify the Raga utilising the Mel-Frequency Cepstrum Coefficient (MFC C), function are key goals of this research is to put into practise and assess. Along with the MFCC function, information Raga detection in music therapy has been proposed using machine learning-based techniques. The chroma and pitch data, with theMFCCfunction are utilised in this method to extract features. ANN classification algorithm for raga suggested method is different from the current one in that it uses the pitch class profile method without taking into account the grade of time information. Kaggle gathered the data in order to assess the suggested approach.With an open-ended approach, the suggested classification method seeks to identify several raga (Yaman,Asvari,Darbari, Bhairavi, and Bageshree). The rate of performance of classifier proposed is about 92.34%.


Raga Identification, Pitch,Pitch Contour, MFCCand Chroma.

Full Text