A. Tjahjanto’s scientific contributions

Development of eastern music like gamelan is far lagged from that of western music because gamelan is still stigmatized as part of traditional arts which must be preserved instead of being analyzed and developed. Therefore development of in depth research concerning gamelan music is needed to bring back the greatness of this music like that in its era (17th-18th century). This research initiates the gamelan sound extraction for music transcription. We applied Least Mean Square - Adaptive Cross Correlation (LACC). ACC was conducted to generate spectral density for music transcription while LMS was utilized to detect instruments which have identical fundamental frequency, in order to avoid over detection. Experiment demonstrates the test performance demonstrates that the proposed method provided 2 - 12% improvement for real gamelan performance comparing to conventional methods such as STFT.

Nowadays, mining of traditional music attracts people's interests in several aspects since the importance of archiving national heritage is emphasized. Unfortunately, there have been very few researches which analyzed traditional music instruments and their performances. Gamelan, one of Indonesia's traditional music instruments, has uniqueness in terms of its hand-made construction which in turn induces variations in frequency, amplitude, and resonance. These conditions have detained the exploration and development of gamelan music itself. This research initiates gamelan sound extraction for music transcription as part of traditional music analysis. Spectral density model was constructed to extract the sound of an instrument from the gamelan ensemble performance by using LPF cross correlation (LPF-CC). The extracted sound was analyzed to generate notations. The experiment demonstrates 5-16% note error rate.