Saron music transcription based on rhythmic information using HMM on Gamelan orchestra

Yoyon K. Suprapto; Yosefine Triwidyastuti

doi:10.12928/TELKOMNIKA.v13i1.295

Saron music transcription based on rhythmic information using HMM on Gamelan orchestra

Yoyon K. Suprapto^*, Yosefine Triwidyastuti

^*Corresponding author for this work

Department of Telecommunications Engineering

STMIK STIKOM Indonesia

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Nowadays, eastern music exploration is needed to raise his popularity that has been abandoned by the people, especially the younger generation. Onset detection in Gamelan music signals are needed to help beginners follow the beats and the notation. We propose a Hidden Markov Model (HMM) method for detecting the onset of each event in the saron sound. F-measure of average the onset detection was analyzed to generate notations. The experiment demonstrates 97.83% F-measure of music transcription.

Original language	English
Pages (from-to)	103-117
Number of pages	15
Journal	Telkomnika (Telecommunication Computing Electronics and Control)
Volume	13
Issue number	1
DOIs	https://doi.org/10.12928/TELKOMNIKA.v13i1.295
Publication status	Published - 2015

Keywords

Gamelan music
Hidden markov model
Music tempo
Music transcription
Onset detection

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10.12928/TELKOMNIKA.v13i1.295

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abstract = "Nowadays, eastern music exploration is needed to raise his popularity that has been abandoned by the people, especially the younger generation. Onset detection in Gamelan music signals are needed to help beginners follow the beats and the notation. We propose a Hidden Markov Model (HMM) method for detecting the onset of each event in the saron sound. F-measure of average the onset detection was analyzed to generate notations. The experiment demonstrates 97.83% F-measure of music transcription.",

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KW - Hidden markov model

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Saron music transcription based on rhythmic information using HMM on Gamelan orchestra

Abstract

Keywords

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