Automatic Synthesis of Notes Based on Carnatic Music Raga Characteristics
In this paper, we propose two methods to automatically generate notes (Swaras) conforming to the rules of Carnatic Music, for a Raga of the user’s choice as the input. The proposed methods are purely statistical in nature. The system requires training examples for learning the probability model of the chosen Raga and no hand-coded rules are required. Hence, it is easy to extend this method to work with a large number of Ragas. Each proposed method involves a Learning Phase and Synthesis Phase. In the Learning Phase, an already existing composition of the desired Raga is used to learn the transition probabilities between swara sequences based on the Raga lakshana characteristics. In the Synthesis Phase, using the previously constructed transition table, swaras are generated for the desired Raga. We describe two methods - one based on First Order Markov Models and the other based on Hidden Markov Models. We also provide comparison of the performance of both the approaches based on feedback from Carnatic experts.
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