DocumentCode :
2427734
Title :
Akshara transcription of mrudangam strokes in Carnatic music
Author :
Kuriakose, Jom ; Chaitanya Kumar, J. ; Sarala, Padi ; Murthy, Hema A. ; Sivaraman, Umayalpuram K.
Author_Institution :
Indian Inst. of Technol., Madras, Chennai, India
fYear :
2015
fDate :
Feb. 27 2015-March 1 2015
Firstpage :
1
Lastpage :
6
Abstract :
Percussion instruments play a significant role in Carnatic music concerts. The percussion artist enjoys a great degree of freedom in improvising within the defined tala structure of a composition. The objective of this paper is to transcribe the improvisations, treating the percussion strokes as syllables or aksharas. Onset detection is performed to segment the waveform at each akshara. Using the transcriptions from the training data, a three-state Hidden Markov Model is built for each akshara. The language model is derived from the training data. Testing is also performed isolated style using onset detection to segment the phrase, and the language model to correct the transcription. Transcription is performed on both concert recordings and studio recordings. This technique yields upto ≈ 96% accuracy on studio recordings and ≈ 76% accuracy for concert recordings. As the mrudangam1 is an instrument that is based on tonic; tonic normalised features, namely, Cent Filterbank Cepstral coefficients are used. It is shown that tonic normalisation helps in transcription across different tonics.
Keywords :
cepstral analysis; channel bank filters; hidden Markov models; musical instruments; natural language processing; Akshara transcription; Carnatic music concerts; Mrudangam strokes; aksharas; cent filterbank cepstral coefficients; composition tala structure; concert recordings; isolated style; language model; onset detection; percussion instruments; percussion strokes; phrase segmentation; studio recordings; syllable; three-state hidden Markov model; tonic normalisation; training data; waveform segmentation; Accuracy; Computational modeling; Databases; Feature extraction; Hidden Markov models; Instruments; Mel frequency cepstral coefficient;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (NCC), 2015 Twenty First National Conference on
Conference_Location :
Mumbai
Type :
conf
DOI :
10.1109/NCC.2015.7084906
Filename :
7084906
Link To Document :
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