Segmentation of Identical and Simultaneously Played Traditional Music Instruments using Adaptive

Yoyon K. Suprapto, Mauridhi H. Purnomo, Mochamad Hariyadi


Nowadays, mining of the musical ensemble has become very crucial since the information inside a musical ensemble is required by any musical contents services. In this research, we introduce Gamelan as one of the Indonesian traditional music instruments as our research objective. To indicate the changes of Gamelan features (i.e. tempo also the hammer struck styles) the segmentation of Gamelan music instruments is required as the music tagging tools. Adaptive LMS is employed for segmenting identical instruments that are played in the concurrent fashion. The target is to find how many instruments are played at the same time or separated by very short time (≤ 1 ms). The experiment results demonstrate robust detection with 0.02 ms accuracy for segmenting identical and simultaneously played Gamelan instruments. These results are employed for indicating the changes of Gamelan features, such as tempo also the hammer struck styles.


component; Adaptive LMS; Gamelan features; Music tagging

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K. Glinos, 1997, “Information Access and Interfaces,” Presentation for the Last Call for the 4th Framework, 29 September, Brussels.”

Sumarsam, 1992, “Cultural Interaction and Musical

Development in Central Java,” The University of Chicago Press.

E. Salleh, 2008, “Wayang kulit,” National Library Board Singapore, Dec.

K.K.T.O. Tetsuro Kitahara, Masataka Goto and H.G. Okuno, 2007, “Instrument Identification in Polyphonic Music: Pitch Weighting to Minimize Influence of Sound Overlaps,” EURASIP Journal on Advance in Signal Processing,vol.

S.S. Haruto Takeda, Takuya Nishimoto, 2003, “Automatic Rhythm Transcription from Multiphonic Midi

Signals,”// .edu/ 652819.html.

M.H.P. Yoyon K Suprapto, Moch Hariadi, 2008, “A Gamelan Sound Segmentation using Inverse Filter,” The 6th Kumamoto University Forum, Nov.

M.H.P. Yoyon K Suprapto, Mochamad Hariadi, 2008, “Gamelan Sound Detection using Cross Correlation,” Seminar on Intelligent Technology and Its Applications, 2008. J.O.S. III, “Physical audio signal processing,” Center for Computer Research in Music and Acoustics (CCRMA), Stanford University, Dec.

B.L. Dhanda, 2003, “Perancangan dan Pembuatan Perangkat Lunak untuk Analisa dan Sintesa Bunyi Gamelan pada Komputer,” Thesis in Electrical Engineering Department ITS.

S.J. Orfanidis, 1988, “Optimum Signal Processing,” acMillan Publishing Company, New York, vol.2nd edition.

S. Haykin, 1996, “Adaptive Filter Theory,” Prentice Hall, ol.3rd edition.



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