Percussion instruments play a significant role in/nCarnatic music concerts. The percussion artist enjoys a great/ndegree of freedom in improvising within the defined tala/nstructure/nof a composition. The objective of this paper is to transcribe the/nimprovisations, treating the percussion strokes as syllables or/naksharas./nOnset detection is performed to segment the waveform at/neach/nakshara/n. Using the transcriptions from the training data,/na three-state Hidden Markov Model is built for each/nakshara/n./nThe language model is derived from the training data. Testing/nis also performed isolated style using onset detection to segment/nthe phrase, and the language model to correct the transcription./nTranscription is performed on both concert recordings and studio/nrecordings. This technique yields upto/n≈/n96%/naccuracy on studio/nrecordings and/n≈/n76%/naccuracy for concert recordings./nAs the mrudangam/n1/nis an instrument that is based on tonic;/ntonic normalised features, namely, Cent Filterbank Cepstral/ncoefficients are used. It is shown that tonic normalisation helps/nin transcription across different tonics.

This research was partly funded by the European Research/nCouncil under the European Unions Seventh Framework Pro-/ngram, as part of the CompMusic project (ERC grant agreement/n267583).