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Titlebook: Artificial Intelligence in Music, Sound, Art and Design; 10th International C Juan Romero,Tiago Martins,Nereida Rodríguez-Fernán Conference

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https://doi.org/10.1007/978-3-662-61480-8complexity is a core concept in computational approaches to aesthetics. Shannon’s information theory provided an objective measure of complexity, which led to the emergence of various informational theories of aesthetics. However, entropy fails to take into account the spatial characteristics of 2D
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https://doi.org/10.1007/978-3-662-61480-8sing individual sound events associated with each cell in a three-dimensional grid. Each sound-event is spatialized depending on the orientation of the listener relative to the three-dimensional model. Users can listen to all cells simultaneously or in sequential slices at will. Conceived to be used
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Horst Müller-Peters,Robert Quinke we expand those approaches by investigating ., which we apply in two case studies to address two key questions: (1) what musical information do chord embeddings capture?; and (2) how might musical applications benefit from them? In our analysis, we show that they capture similarities between chords
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https://doi.org/10.1007/978-3-662-58328-9nitions, such as complexity in physical systems (entropy), algorithmic measures of information complexity and the field of “complex systems”. We apply a series of different complexity measures to three different generative art datasets and look at the correlations between complexity and individual a
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