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Gamelan Composer: a Rule-Based Interactive Melody Generator for Gamelan Music

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A rule-based method and a note-by-note generation technique have been proposed to develop a model of an interactive melody generator. The task of the model has been to assist user creating a melody in form of a note sequence. A set of notes candidate has been generated by the system as a recommendation for user to arrange a note sequence. The rules to set the recommendation have been constructed by identifying melodic features using a sequential mining algorithm called Apriori based on Functions in a Sequence (AFiS) algorithm. The experiment has been conducted by developing Gamelan Composer, an interactive melody generator system for gamelan music, a traditional music from Java, Indonesia. Two sets of rules have been defined based on notes prunes technique, which have been a 2-itemset prune and a tier prune, and then they have been implemented into two different systems. The evaluation has been conducted using expert test to judge note sequences generated by users in the experimental groups. The results show that the proposed model can assist users creating a note sequence that has the characteristics of a gamelan melody, and the tier prune rules have generated a note sequence that has the characteristics of gamelan melody, which has been better than the 2-itemset prune rules.
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Rule-Based; Interactive Melody Generator; Computer-Aided Composition; AFiS Algorithm; Gamelan

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E.R. Miranda, Composing Music with Computers, Focal Press, Burlington, 2004.

J.D. Fernández, and F. Vico, AI methods in algorithmic composition: A comprehensive survey, J. Artific. Intell. Res. (2013), 513–582, 2013.

G. Nierhaus, Algorithmic Composition: Paradigms of Automated Music Generation. Springer, 2009.

D. Herremans, C-H. Chuan, E. Chew, A Functional Taxonomy of Music Generation Systems, ACM Computing Surveys, Vol. 50, No. 5, Article 69. 2017, 1-30, 2017.

M. Scirea, G.A.B. Barros, N. Shaker, J. Togelius, SMUG: Scientific Music Generator, International Conference on Computational Creativity (ICCC 2015), 204-211, 2015.

A.S. Ramanto, and N.U. Maulidevi, Markov Chain based Procedural Music Generator with User Chosen Mood Compatibility, International Journal of Asia Digital Art and Design Association, Volume 21 Issue 1, 19-24, 2017.

C. Roig, L.J. Tardón, I. Barbancho, A.M. Barbancho, A non-homogeneous beat-based harmony Markov model, Knowledge-Based Systems, Volume 142, 15 February 2018, 85-94, 2018.

N. Otani, D. Okabe, M. Numao, Generating a Melody Based on Symbiotic Evolution for Musicians’ Creative Activities, in Proceedings of the Genetic and Evolutionary Computation Conference, Kyoto, Japan — July 15 - 19, 2018, 197-204, 2018.

V. Padilla, and D. Conklin, Generation of Two-Voice Imitative Counterpoint from Statistical Models, International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 5, No. 3, 2018, 22-32, 2018.

H. Young, A Categorial Grammar for Music and Its Use in Automatic Melody Generation, in Proceedings of the 5th ACM SIGPLAN International Workshop on Functional Art, Music 2017, Modeling, and Design, 1-9, 2017.

Hastuti, K., Azhari, A., Musdholifah, A., Supanggah, R., Building Melodic Feature Knowledge of Gamelan Music Using Apriori Based on Functions in Sequence (AFiS) Algorithm, (2016) International Review on Computers and Software (IRECOS), 11 (12), pp. 1127-1137.

Hastuti, K., Azhari, A., Musdholifah, A., Supanggah, R., Rule-Based and Genetic Algorithm for Automatic Gamelan Music Composition, (2017) International Review on Modelling and Simulations (IREMOS), 10 (3), pp. 202-212.

H. Tsushima, E. Nakamura, K. Itoyama, K. Yoshii, Interactive Arrangement of Chords and Melodies based on a Tree-Structured Generative Model, in Proceedings of the 19th ISMIR Conference, Paris, France, September 23-27, 2018, 145-151, 2018.

P. Talbot, C. Agon, P. Esling, Interactive Computer-Aided Composition with Constraints, 43rd International Computer Music Conference (ICMC 2017), Oct 2017, Shanghai, China, hal-01577898, 2017.

M. Farzaneh, and R.M. Toroghi, Melody Generation using an Interactive Evolutionary Algorithm, arXiv:1907.04258 [cs.NE], 2019.

M.A.K. Papakostas, A. Floros, M.N. Vrahatis, Interactive music composition driven by feature evolution, SpringerPlus, 5: 826, 1-38, 2016.

Li, S., Jang, S., Sung, Y., Automatic Melody Composition Using Enhanced GAN, Mathematics 2019, 7(10), 883.

Duarte, A.E.L., Algorithmic Interactive Music Generation in Videogames, SoundEffects, vol. 9. No. 1, 2020.

T. Gifford, S. Knotts, J. McCormack, S.K. Matthew, Y. King, M. d’Inverno, Computational systems for music improvisation, Digital Creativity, 29:1, 19-36, 2018.

C. Poncelet, and F. Jacquemard, Model Based Testing of an Interactive Music System, in Proceedings of the 30th Annual ACM Symposium on Applied Computing, April 13-17, 2015, Salamanca, Spain, 1759-1764, 2015.

Roberts A., Engel J., Oore, S., Eck, D., Learning Latent Representations of Music to Generate Interactive Musical Palettes, Music Interfaces for Listening and Creation (MILC) 18, March, 2018, Tokyo, Japan, 2018.

Polo, A., Sevillano, X., Musical Vision: an interactive bio-inspired sonification tool to convert images into music, Journal of Multimodal User Interfaces, vol. 13, 231–243, 2019.

K. Hastuti, A.M. Syarif, A.Z. Fanani, A.R. Mulyana, Natural Automatic Musical Note Player using Time-Frequency Analysis on Human Play, Telkomnika (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019, 235-245, 2019.


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