Abstract
The aim of computer-aided musical orchestration is to find a combination of musical instrument sounds that approximates a target sound. The difficulty arises from the complexity of timbre perception and the combinatorial explosion of all possible instrument mixtures. The estimation of perceptual similarities between sounds requires a model capable of capturing the multidimensional perception of timbre, among other perceptual qualities of sounds. In this work, we use an artificial immune system (AIS) called opt-aiNet to search for combinations of musical instrument sounds that minimize the distance to a target sound encoded in a fitness function. Opt-aiNet is capable of finding multiple solutions in parallel while preserving diversity, proposing alternative orchestrations for the same target sound that are different among themselves. We performed a listening test to evaluate the subjective similarity and diversity of the orchestrations.
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Notes
- 1.
- 2.
Access http://goo.gl/weHaHI to see the test and listen to the sounds.
- 3.
Access http://goo.gl/4l9NqX to listen to the target sounds and results.
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Acknowledgments
This work is financed by the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project “UID/EEA/50014/2013.” The authors would like to thank the integrated masters program in Electrical and Computer Engineering (MIEEC) from the University of Porto (FEUP) for the financial support.
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Abreu, J., Caetano, M., Penha, R. (2016). Computer-Aided Musical Orchestration Using an Artificial Immune System. In: Johnson, C., Ciesielski, V., Correia, J., Machado, P. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2016. Lecture Notes in Computer Science(), vol 9596. Springer, Cham. https://doi.org/10.1007/978-3-319-31008-4_1
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