Abstract

Raga is the central melodic concept in Indian classical music and its automatic recognition is an important research area in computational musicology. It has several applications like indexing music, comparing and classifying music, Music Information Retrieval and pedagogy of music. Musical note extraction is the first logical step in the process of creating computational models of ragas. This paper proposes a method for extracting musical notes (swaras) from audio recordings of South Indian Classical music, based on a special kind of Artificial Neural Network known as Kohonen’s Self Organizing Feature Map (SOM).

References

• Chordia, P., Rae, A. Raag Recognition using Pitch-Class and Pitch-Class Dyad Distributions. Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR), Vienna, Austria, 2007
• Koduri, G.K., Miron M., Serra J., Serra, X. Computational approaches for the understanding of melody in carnatic music. 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Florida, USA
• Krishnaswamy, A. On the Twelve Basic Intervals in South Indian Classical Music. Audio Engineering Society Convention Paper, 115th Convention, 2003 October 10-13, New York
• Klapuri, A.P. Automatic Music Transcription as We Know it Today. Journal of New Music Research. 2004, Vol. 33, No. 3
• Lapp, D.R. The Physics of Music and Musical Instruments. Wright Center for Innovative Science Education, Tufts University, Medford, Massachusetts
• Chakravorty, J., Mukherjee, B., Datta, A.K. Some studies on machine recognition of ragas in Indian classical music. Journal of Acoustic Society of India, Vol. XVII(3&4)
• Sahasrabuddhe, H.V., Upadhye, R. On the Computational Model of Raag Music of India. Workshop on AI and Music: 10th European Conference on AI, Vienna
• Pandey, G., Mishra, C., Ipe, P. Tansen: A system for automatic raga identification. Indian International Conference on Artificial Intelligence, Hyderabad, India, 2003
• Sinith, M., Rajeev, K. Hidden Markov model based recognition of musical pattern in South Indian Classical Music. IEEE International Conference on Signal and Image Processing, Hubli, India, 2003
• Sridhar, R., Geetha, T. Raga identification of Carnatic music for Music Information Retrieval. International Journal of Recent Trends in Engineering, Vol. 1(1), 2009
• Shetty, S., Achary, K.K. Raga mining of Indian music by extracting Arohana-Avarohana pattern. International Journal of Recent Trends in Engineering, Vol. 1(1), 2009
• Belle, S., Joshi, R., Rao, P. Raga identification by using Swara intonation. Journal of ITC Sangeet Research Academy, Vol. 23, 2009
• Koduri, G.K., Gulati, S., Rao, P., Serra, X. Raga Recognition based on Pitch Distribution Methods. Journal of New Music Research, Vol. 41(4), 2012
• Lippmann, R.P. An Introduction' to Computing with Neural Nets. IEEE ASSP Magazine, April, 1987
• Wasserman, P.D. Neural Computing: Theory and Practice. Van Nostrand Reinhold, Newyork
• Kohonen, T. Self-Organization and Associative Memory. Springer-Verlag, Berlin (1989)
• Mayer, R., Frank, J., Rauber, A. Analytic Comparison of Audio Feature Sets using Self-Organizing Maps. Workshop on Exploring Musical Information Spaces, 2009, Greece
• Unnikrishnan, G. Extraction of Musical Notes from Sound Signals for Identification of Carnatic Ragas. Computing and Communication, Narosa Publishing House, New Delhi, 2012, Chapter 21, pp 143-149