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ITS » Paper and Presentation » Teknik Elektro - Telematika S2
Posted by dee@its.ac.id at 10/12/2013 12:59:13  •  1295 Views


DETEKSI ONSET SINYAL BALUNGAN MENGGUNAKAN HIDDEN MARKOV MODEL UNTUK BEAT TRACKING MUSIK GAMELAN

BALUNGAN SIGNAL ONSET DETECTION USING HIDDEN MARKOV MODEL FOR GAMELAN MUSIC BEAT TRACKING

Author :
TRIWIDYASTUTI, YOSEFINE ( 2211206004 )




ABSTRAK

Penjajakan ketukan sinyal Balungan pada musik Gamelan memainkan peran penting dalam aplikasi pengolahan sinyal musik seperti penjajakan tempo musik dan transkripsi musik atau proses menotasikan sinyal musik. Karena adanya keragaman karakter suara Gamelan yang dipengaruhi oleh banyak hal antara lain cara pembuatan peralatan yang kurang sempurna dan cara pemukulan peralatan yang berdasar kira-kira serta permainan musik Gamelan yang dimainkan secara bersamaan dan tempo yang berubah-ubah sinyal musik Gamelan memiliki kriteria analisa suara yang lebih rumit dibandingkan analisa peralatan musik barat. Pada penelitian ini penjajakan ketukan dilakukan dengan menggunakan deteksi onset berbasis metode Hidden Markov Model HMM untuk mendapatkan waktu terjadinya ketukan dari sinyal Balungan pada musik Gamelan. Metode HMM memungkinkan adanya penggabungan informasi musik ke dalam deteksi ketukan sehingga hasil deteksi diharapkan lebih teliti dan lebih sesuai dengan struktur musik Gamelan. Dari beberapa hasil percobaan deteksi onset dengan metode HMM menghasilkan kinerja yang cukup tinggi hingga 89 pada data lagu permainan instrumen tunggal. Sedangkan pada data lagu dengan banyak instrumen ketelitiannya mencapai 73. Namun pada data lagu instrumen tunggal yang sering berubah-ubah temponya detektor HMM mempunyai kinerja hingga 95. Sebagai hasil perbandingan kinerja metode HMM juga dibuktikan lebih unggul dari metode Spectral Flux yang biasa diterapkan pada alat musik perkusif. Pada beberapa data lagu baik sintetik maupun akustik metode HMM menghasilkan ketelitian lebih baik 10 dari metode Spectral Flux.


ABSTRACT

Gamelan music beat tracking plays important role in signal processing applications for example music transcription that could help beginners learn how to play Gamelan instruments. Because of various characters in Gamelan instrument productions and playing styles like in orchestra Gamelan signal analysis is more difficult than western music analysis. In this research we use beat tracking method with onset detection based on Hidden Markov Model HMM approach to track the time possibilities of Balungan beat occurrence in Gamelan music signal. HMM method allows any musical information to be combined in detection process such that we can get a result that is more accurate and suitable with Gamelan music structure. In several results HMM method yielded performance with average value 89 for single-instrument music signal and 73 for multi-instrument signal. Nevertheless in a variated tempo music signal from single-intrument experiment HMM method obtained 95 of accuracy. As evaluation HMM methods performance was compared with Spectral Flux method common method used in percussive instruments. In a variated music signal HMM method superior more 10 than Spectral Flux.



KeywordsSinyal musik Gamelan; Tempo musik; Penjajakan ketukan; Deteksi onset; Hidden Markov Model
 
Subject:  Pengukuran bunyi
Contributor
  1. DR. Ir. Yoyon Kusnendar Suprapto, M.Sc.
Date Create: 31/01/2013
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-paper-22021130002892
Collection ID: 22021130002892
Call Number: RTE 620.2 Tri d


Source
Paper and Presentation of Electrical Engineering, RTE 620.2 Tri d, 2013

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Copyright @2013 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




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