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JRM Vol.29 No.1 pp. 137-145
doi: 10.20965/jrm.2017.p0137
(2017)

Paper:

Wayang Robot with Gamelan Music Pattern Recognition

Tito Pradhono Tomo*, Alexander Schmitz*, Guillermo Enriquez**, Shuji Hashimoto**, and Shigeki Sugano*

*Department of Modern Mechanical Engineering, School of Creative Science and Engineering, Waseda University
3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan

**Department of Applied Physics, School of Advanced Science and Engineering, Waseda University
3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan

Received:
August 7, 2016
Accepted:
October 17, 2016
Published:
February 20, 2017
Keywords:
music information retrieval, machine learning, intelligent machine, wayang kulit, intangible culture
Abstract

Wayang Robot with Gamelan Music Pattern Recognition

Wayang robot

This paper proposes a way to protect endangered wayang puppet theater, an intangible cultural heritage from Indonesia, by turning a robot into a puppeteer successor. We developed a seven degrees-of-freedom (DOF) manipulator to actuate the sticks attached to the wayang puppet body and hands. The robot can imitate 8 distinct human puppeteer’s manipulations. Furthermore, we developed a gamelan music pattern recognition, towards a robot that can perform based on the gamelan music. In the offline experiment, we extracted energy (time domain), spectral rolloff, 13 Mel-frequency cepstral coefficients (MFCCs), and the harmonic ratio from 5 s long clips, every 0.025 s, with a window length of 1 s, for a total of 2576 features. Two classifiers (3 layers feed-forward neural network (FNN) and multi-class Support Vector Machine (SVM)) were compared. The SVM classifier outperformed the FNN classifier with a recognition rate of 96.4% for identifying the three different gamelan music patterns.

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Last updated on Sep. 20, 2017