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Reseach Article

Automatic Music Note Transcription System using Artificial Neural Networks

Published on February 2013 by Ramya S., T. K. Padmashree
International Conference on Electronic Design and Signal Processing
Foundation of Computer Science USA
ICEDSP - Number 4
February 2013
Authors: Ramya S., T. K. Padmashree
9cfe91e8-f4ca-45af-8f1e-badf3e56c92a

Ramya S., T. K. Padmashree . Automatic Music Note Transcription System using Artificial Neural Networks. International Conference on Electronic Design and Signal Processing. ICEDSP, 4 (February 2013), 11-15.

@article{
author = { Ramya S., T. K. Padmashree },
title = { Automatic Music Note Transcription System using Artificial Neural Networks },
journal = { International Conference on Electronic Design and Signal Processing },
issue_date = { February 2013 },
volume = { ICEDSP },
number = { 4 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 11-15 },
numpages = 5,
url = { /specialissues/icedsp/number4/10370-1029/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Electronic Design and Signal Processing
%A Ramya S.
%A T. K. Padmashree
%T Automatic Music Note Transcription System using Artificial Neural Networks
%J International Conference on Electronic Design and Signal Processing
%@ 0975-8887
%V ICEDSP
%N 4
%P 11-15
%D 2013
%I International Journal of Computer Applications
Abstract

In this work, we propose a method to identify and transcript the note of a Carnatic music signal. The main motive behind note transcription is that, it can be used as a good basis for music note information retrieval of Carnatic music songs or Film songs based on Carnatic music. The input monophonic music signal is analysed and made to pass through a signal frequency extracting algorithm. The frequency components of the signal are then mapped into the swara sequence, which could be used to determine the Raga of the particular song and can be used in Carnatic music training institutes to verify the correctness of the Carnatic music note.

References
  1. Sriram, P. 1990 . A Karnatic Music primer.
  2. K. Balasubramanian,"Combinatorial Enumeration of Ragas (Scales Of Integer Sequences) of Indian Music", Journal of Integer Sequences, Vol. 5 (2002), Article 02. 2. 6.
  3. Sambamurthy, 1982. South Indian Music, vol. 4.
  4. Carnatic Music Origin & Development, http://www. chembur. com/carnatic/.
  5. Varadarangan, 2000. Shruthi Lakshna Prakashini.
  6. Sridhar, R. and Geetha, T. V. 2006. Swara identification of Carnatic music. In Proceedings of the IEEE Conference on Information Tecnology.
  7. Sridhar, R. and Geetha, T. V. 2008. Music Information Retrieval of Carnatic Songs Based on Carnatic Music Singer Identification. In Proceedings of the IEEE conference on Computer and Electrical Engineering.
  8. Pandey, G. ,Mishra, C. , Ipe, P. 2003. Tansen: A System for Automatic Raga identification. In Proceedings of the 1st Indian International Conference on Artificial Intelligence, Hyderabad,1350-1363.
  9. Vir, R. 1999. Theory of Indian Music.
  10. Rao, P. and Anand Raju, 2002. Building a melody retrieval system. In Proceedings of the National Conference on Communications, IIT Bombay.
  11. Maarten G. 2005, Melody retrieval based on the Implication Realization model. MIREX 2005
  12. Kent,R. and Read, C. 1995. The Acoustic analysis of Speech.
  13. Furui, and Sadaoki, 2000. Digital Speech Processing, Synthesis, and Recognition.
  14. Rabiner,L. R. , and Schafer, R. W. 1978. Digital Processing of Speech Signals.
  15. Berthold, M. , Thiel, K. , 2007. Artificial Neural Networks: Local Basis Function Networks: RBF, PNN Neuro-Fuzzy / Fuzzy-Neuro, VL 7.
  16. Jang, J. R. , Sun, C. and Mizutani, E. , 1997. Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence.
  17. Nikola, K. , Kasabov, 1998. Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering.
  18. Ramya, L. , Padmashri,T. K ,2009. Carnatic Music Note Identification using DSP and Neural Networks. In Proceedings of Int. Conf . Electronic Design and Signal Processing, MIT , Manipal.
  19. H. Demuth and M. Beale. Neural Network TOOLBOX User's Guide. For use with MATLAB. The Math Works lne. . (1998)
Index Terms

Computer Science
Information Sciences

Keywords

Audio Signal Processing autocorrelation Carnatic Music probalistic Neural Network Pitch Swara Shruthi