Automatic Identification of Instrument Type in Music Signal Using Wavelet and MFCC

In this work, we have presented a simple but novel scheme for Automatic Identification of Instrument Type present in the Music Signal. A hierarchical approach has been devised by observing the characteristics of different types of instruments. Accordingly, suitable features are deployed at different stages. In the first stage, wavelet based features are used to subdivide the instruments into two groups which are then classified using MFCC based features at second stage. RANSAC has been used to classify the data. Thus, a system has been proposed which unlike the previous system relies on very low dimensional feature.

[1]  J C Brown,et al.  Feature dependence in the automatic identification of musical woodwind instruments. , 2001, The Journal of the Acoustical Society of America.

[2]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[3]  Stephen Cranefield,et al.  A Study on Feature Analysis for Musical Instrument Classification , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[4]  Constantine Kotropoulos,et al.  Musical Instrument Classification using Non-Negative Matrix Factorization Algorithms and Subset Feature Selection , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[5]  Emanuele Pollastri,et al.  Musical Instrument Timbres Classification with Spectral Features , 2003, EURASIP J. Adv. Signal Process..

[6]  Bibhas Chandra Dhara,et al.  Instrumental/song classification of music signal using RANSAC , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[7]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[8]  Tong Zhang,et al.  Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing , 2001 .

[9]  B. S. Manjunath,et al.  The multiRANSAC algorithm and its application to detect planar homographies , 2005, IEEE International Conference on Image Processing 2005.

[10]  Tadeusz Czaszejko,et al.  Automatic Recognition of Isolated Monophonic Musical Instrument Sounds using kNNC , 2005, Journal of Intelligent Information Systems.

[11]  Perfecto Herrera-Boyer,et al.  Automatic Classification of Musical Instrument Sounds , 2003 .

[12]  Rafael C. González,et al.  Digital image processing, 3rd Edition , 2008 .

[13]  Xavier Rodet,et al.  MUSICAL INSTRUMENT IDENTIFICATION IN CONTINUOUS RECORDINGS , 2004 .