A review of raga based music classification and music information retrieval (MIR)

This paper introduces the Raga Based Music Classification as a part of Music Information Retrieval (MIR) systems for retrieving musical information. The music has been more than just a sound that entertains us. MIR users like musicology researchers, musicians, music learners, music therapists, etc., require not just the sound but the actual strength of the music that controls our body, motivates us, cures mental illness, etc. The backbone of any form of music is its raga. A raga is a particular combination of notes with certain laws which, when carefully observed, preserves and safeguards their integrity and create wonders in music. The existing MIR systems and audio search engines concentrate on content based audio mining and not ragas. This paper discusses the classification of ragas and how it differs in Carnatic, Hindustani and Western musical forms. It also describes the various features that can be extracted from an audio data to represent a raga. Finally, we propose a system architecture to perform raga based classification of music.

[1]  FooteJonathan.  An overview of audio information retrieval , 1999 .

[2]  Vasudeo G. Apte.  The Concise Sanskrit-English Dictionary , 1986 .

[3]  Zbigniew W. Ras,et al.  Music Instrument Estimation in Polyphonic Sound Based on Short-Term Spectrum Match , 2009, Foundations of Computational Intelligence.

[4]  Jonathan Foote,et al.  An overview of audio information retrieval , 1999, Multimedia Systems.

[5]  Keith D. Martin,et al.  TOWARD AUTOMATIC SOUND SOURCE RECOGNITION: IDENTIFYING MUSICAL INSTRUMENTS , 1998 .

[6]  Lie Lu,et al.  Content analysis for audio classification and segmentation , 2002, IEEE Trans. Speech Audio Process..

[7]  Arvindh Krishnaswamy,et al.  Application of pitch tracking to South Indian classical music , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[8]  Lie Lu,et al.  A robust audio classification and segmentation method , 2001, MULTIMEDIA '01.

[9]  Nicu Sebe,et al.  Content-based multimedia information retrieval: State of the art and challenges , 2006, TOMCCAP.

[10]  Arvindh Krishnaswamy,et al.  Application of pitch tracking to South Indian classical music , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[11]  Mark R. Every,et al.  A SPECTRAL-FILTERING APPROACH TO MUSIC SIGNAL SEPARATION , 2004 .

[12]  Ram Avtar.  Theory of Indian Music , 1999 .

[13]  Changshui Zhang,et al.  Separation of Voice and Music by Harmonic Structure Stability Analysis , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[14]  Parag Chordia.  Automatic Raag Classification of Pitch-tracked Performances Using Pitch-class and Pitch-class Dyad Distributions , 2006, ICMC.

[15]  Surendra Shetty,et al.  Raga Mining of Indian Music by Extracting Arohana-Avarohana Pattern , 2009 .

[16]  R. Sridhar.  Raga Identification of Carnatic music for Music Information Retrieval , 2009 .

[17]  D.J. Schneck,et al.  The role of music in physiologic accommodation , 1999, IEEE Engineering in Medicine and Biology Magazine.