Gamelan Music Onset Detection based on Spectral Features
Abstract: This research
detects onsets of percussive instruments by examining the performance on the
sound signals of gamelan instruments as one of
traditional music instruments in Indonesia. Onset plays important role
in determining musical rythmic structure, like beat, tempo, measure, and is
highly required in many applications of music information retrieval. Four onset
detection methods that employ spectral features, such as magnitude, phase, and
the combination of both are compared in this paper. They are phase slope (PS),
weighted phase deviation (WPD), spectral flux (SF), and rectified complex
domain (RCD). Features are extracted by representing the sound signals into
time-frequency domain using overlapped Short-time Fourier Transform (STFT) and
by varying the window length. Onset detection functions are processed through
peak-picking using dynamic threshold. The results showed that by using suitable
window length and parameter setting of dynamic threshold, F-measure which is
greater than 0.80 can be obtained for certain methods.
Author: Diah P. Wulandari,
Aris Tjahyanto, Yoyon K. Suprapto
Journal Code: jptkomputergg130120
