Composing Bossa Nova by Evolutionary Computation

Wen, Yu-Wei; Ting, Chuan-Kang

doi:10.1109/ijcnn48605.2020.9207713

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…By introducing this technique, they ensure that both, notes and chords, are closely related along all the training steps. Recently, Yu-Wei Wen and Chuan-Kang Ting [34] utilized genetic algorithms in developing a chord generator that follows the Bossa Nova style.…”

Section: Chord Accompanimentmentioning

confidence: 99%

Applications of Computational Intelligence in Computer Music Composition

Siphocly

Salem

El-Horabty

2021

IJICIS

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Engaging computers in composing musical pieces is a challenging and trending field of research. The musical tasks that can be performed or aided by computers' computational powers, are numerous. This paper is concerned with applications of computational intelligence in music composition. Its main objective is to survey various computational intelligence techniques for performing miscellaneous music composition tasks. To achieve this objective, we first define each music composition task, then we discuss the recent applications of each, and the techniques adopted in them. We also highlight the most suitable techniques for performing each task. Our study shows that the most suitable techniques for human composers imitative systems are case-based reasoning and artificial neural networks. It is also shown that Markov models are more suitable for predicting musical notes based on the given previous notes. Genetic algorithms excel in chord progressions generation. Deep neural networks are clever at capturing temporal information of a musical piece. The state-of-the-art generative adversarial networks produce music as close as possible to real compositions. At the end of this study, we shed the light on many future research directions in the field of computer music composition.

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Section: Chord Accompanimentmentioning

confidence: 99%