Extracted Energies; Intangible Cultural Heritages; Intangible Culture; Intelligent Machine; Learning Systems; Machine Learning; Mel-frequency Cepstral Coefficients; Multi-class Support Vector Machines; Music Information Retrieval; Pattern Recognition; Puppet Theaters; Robots; Speech Recognition; Support Vector Machines; Wayang Kulit;

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013880391&doi=10.20965%2fjrm.2017.p0137&partnerID=40&md5=4ca47c7a752abe03a80b8599ff3bc2c2

10.20965/jrm.2017.p0137

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-offreedom (DOF) manipulator to actuate the sticks attached to the wayang puppet body and hands. The robot can imitate 8 distinct human puppeteer’smanipulations. 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 SVMclassifier outperformed the FNN classifier with a recognition rate of 96.4%for identifying the three different gamelan music patterns.