Carnatic Music Identification of Melakarta Ragas through Machine and Deep Learning using Audio Signal Processing

This study focuses on predicting the raga, which is a fundamental aspect of Indian classical music, from a given .wav file using machine learning and deep learning models. The approach involves audio processing and feature extraction with the Librosa library. Finally, the system is trained and tested on the extracted data to predict the raga. This study has various applications, such as music education, therapy, and synthesis. Predicting the raga of a given audio clip can be challenging, as it requires a deep understanding of the underlying musical structure and nuances of Indian classical music. However, with machine learning and deep learning techniques, it has become possible to develop automated systems that can accurately predict the raga from an audio file. The proposed project focuses on developing such a system using machine learning and deep learning models. The study involves audio processing and feature extraction using the Librosa library, a widely used Python package for music analysis. Librosa provides various tools for audio processing, such as audio loading, time and frequency domain analysis, and feature extraction.