Abstract
The primary objective of work is to build an expert evaluation and feedback system which can be used as tutoring software for novice learners of Hindustani Classical Music (HCM). Computational Musicology from the perspective of HCM deals with Raga recognition and music generation, however to the best of our knowledge there is no work to understand the structure of Raga and evaluate rendered song based on Raga conventions. We propose a model as tutoring system which listens to the vocal input of the singer and evaluate it based on the rules/conventions of Raga. Further, the expert system also provides correct suggestions for the error note. In our model we propose the use of transition matrix for note evaluation and variable length n-gram modeling for error correction. The performance evaluation of error correction module is done using accuracy and aesthetic correctness scale.
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Gajjar, K., Patel, M. (2020). RAAGANG—A Proposed Model of Tutoring System for Novice Learners of Hindustani Classical Music. In: Tuba, M., Akashe, S., Joshi, A. (eds) ICT Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 1077. Springer, Singapore. https://doi.org/10.1007/978-981-15-0936-0_54
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DOI: https://doi.org/10.1007/978-981-15-0936-0_54
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