Anticipatory timing in algorithmic rhythm generation
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Author(s)
Gifford, Toby
Brown, Andrew R.
Griffith University Author(s)
Year published
2010
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Generative music algorithms frequently operate by making musical decisions in a sequence, with each step of the sequence incorporating the local musical context in the decision process. The context is generally a short window of past musical actions. What is not generally included in the context is future actions. For real-time systems this is because the future is unknown. Offline systems also frequently utilise causal algorithms either for reasons of efficiency [1] or to simulate perceptual constraints [2]. However, even real-time agents can incorporate knowledge of their own future actions by utilising some form of planning. ...
View more >Generative music algorithms frequently operate by making musical decisions in a sequence, with each step of the sequence incorporating the local musical context in the decision process. The context is generally a short window of past musical actions. What is not generally included in the context is future actions. For real-time systems this is because the future is unknown. Offline systems also frequently utilise causal algorithms either for reasons of efficiency [1] or to simulate perceptual constraints [2]. However, even real-time agents can incorporate knowledge of their own future actions by utilising some form of planning. We argue that for rhythmic generation the incorporation of a limited form of planning - anticipatory timing - offers a worthwhile trade-off between musical salience and efficiency. We give an example of a real-time generative agent - the Jambot - that utilises anticipatory timing for rhythmic generation. We describe its operation, and compare its output with and without anticipatory timing.
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View more >Generative music algorithms frequently operate by making musical decisions in a sequence, with each step of the sequence incorporating the local musical context in the decision process. The context is generally a short window of past musical actions. What is not generally included in the context is future actions. For real-time systems this is because the future is unknown. Offline systems also frequently utilise causal algorithms either for reasons of efficiency [1] or to simulate perceptual constraints [2]. However, even real-time agents can incorporate knowledge of their own future actions by utilising some form of planning. We argue that for rhythmic generation the incorporation of a limited form of planning - anticipatory timing - offers a worthwhile trade-off between musical salience and efficiency. We give an example of a real-time generative agent - the Jambot - that utilises anticipatory timing for rhythmic generation. We describe its operation, and compare its output with and without anticipatory timing.
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Conference Title
Proceedings of the Australasian Computer Music Conference 2010
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Copyright Statement
© The Author(s) 2010. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this conference please refer to the conference's website or contact the authors.
Subject
Information and Computing Sciences not elsewhere classified