Modal analysis and transcription of strokes of the mridangam using non-negative matrix factorization
Modal analysis and transcription of strokes of the mridangam using non-negative matrix factorization
In this paper we use a Non-negative Matrix Factorization/n(NMF) based approach to analyze the strokes of the mri-/ndangam, a South Indian hand drum, in terms of the normal/nmodes of the instrument. Using NMF, a dictionary of spectral/nbasis vectors are first created for each of the modes of the/nmridangam. The composition of the strokes are then studied/nby projecting them along the direction of the modes using/nNMF. We then extend this knowledge of each stroke in terms/nof its basic modes to transcribe audio recordings. Hidden/nMarkov Models are adopted to learn the modal activations for/neach of the strokes of the mridangam, yielding up to/n88,40%/naccuracy during transcription.
This research/nwas partly funded by the European Research Council under the/nEuropean/nUnions Seventh Framework Program, as part of the CompMusic project/n(ERC grant agreement 267583).
Modal Analysis, Mridangam, Hidden Markov models, Automatic transcription, Non-negative Matrix Factorization
Modal Analysis, Mridangam, Hidden Markov models, Automatic transcription, Non-negative Matrix Factorization
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