Automatic Music Generation of Indian Classical Music based on Raga

The use of machine learning algorithms for the generation of new music has garnered increasing interest in recent years. With the aim of creating music that does not currently exist in the market, various machine learning techniques are being employed, including LSTM, RBM, GCA, FSM, and GAN. This research paper focuses specifically on the application of Wasserstein Generative Adversarial Networks (WGANs) for the generation of Indian classical music based on raga. The study uses MIDI piano music as input and trains the WGAN on a dataset of Indian classical music recordings. The results of the study indicate that the WGAN is capable of producing new music that is stylistically and acoustically similar to the Indian classical music present in the training dataset. Additionally, the generated music was found to be comparable to human-generated music. This study highlights the potential success of utilizing WGANs for creating music in the Indian classical genre, based on raga.