Symbolic Representation-based Melody Extraction using Multiclass Classification for Traditional Javanese Compositions

Syarif, Arry Maulana and Hastuti, Khafiizh and Azhari, Azhari and Suprapto, Suprapto (2021) Symbolic Representation-based Melody Extraction using Multiclass Classification for Traditional Javanese Compositions. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 12 (10). pp. 128-137. ISSN 2158-107X

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Abstract

Traditional Javanese compositions contain melodies and skeletal melodies. Skeletal melodies are an extraction form of melodies. The melody extraction problem is similar to the chord detection in Western music, where chords are extracted from a melody. This research aims to develop a melody extraction system for traditional Javanese compositions. Melodies which have a time series data structure were designed as a part of the supervised learning problem to be solved using the pattern recognition technique and the Feed-Forward Neural Networks method. The melody data source uses a symbolic format in the form of sheet music. The beats in melodies data are used as the input and notes in skeletal melodies are used as the target. An FFNN multi-class classifier was built with six classes as the targets, where the class represents notes of the musical scale system. The network evaluation was conducted using accuracy, precision, recall, specificity and F-1 score measurements.

Item Type: Article
Uncontrolled Keywords: Melody extraction; symbolic representation-based; multiclass classification; feed-forward neural network; Gamelan
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Mathematics and Natural Sciences > Computer Science & Electronics Department
Depositing User: Sri JUNANDI
Date Deposited: 21 Oct 2024 01:37
Last Modified: 21 Oct 2024 01:37
URI: https://ir.lib.ugm.ac.id/id/eprint/9084

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