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.
We present a scoping review of biosensors appropriation as control structures in interactive music systems (IMSs). Technical and artistic dimensions promoted by transdisciplinary approaches, ranging from biomedicine to musical performance and interaction design fields, support a taxonomy for biosensor-driven IMSs. A broad catalog of 70 biosensor-driven IMSs, ranging in publication dates from 1965 to 2019, was compiled and categorized according to the proposed taxonomy. From the catalog data, we extrapolated representative historical trends, notably to critically verify our working hypothesis that biosensing technologies are expanding the array of control structures within IMSs. Observed data show that our hypothesis is consistent with the historical evolution of the biosensor-driven IMSs. From our findings, we advance future challenges for novel means of control across humans and machines that should ultimately transform the agents involved in interactive music creation to form new corporalities in extended performative settings.
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