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Continuation- Musical Note Prediction Through Analysis.

Hunt, Samuel

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Abstract

This paper explores the automatic continuation of melod-ic passages, based on analyses of trends in existing musi-cal corpora, and the challenges of integrating generative processes with manual composition practices and aesthet-ics. While music composition is a personal creative ex-ploration, probability can be used to model the develop-ment of musical pieces.
The papers central theory, referred to as continua-tion, looks to find likely notes that can continue a given input sequence, with the results bound to a probabilistic model. Three methods of continuation are used to gener-ate new content. The first considers composing music using a call-and-response model of interaction with single note prediction. The second considers how the output from the initial process can be fed back as input to con-tinue generating sequences of arbitrary length. The third is a conceptual model that addresses some of the issues with the first two models, also highlighting a powerful extension that utilizes the time domain. A user survey is presented that gauges the musicality of these methods, evaluating the perceived levels of computer-influenced composition. The results of this are discussed along with proposals for future research in this field.

Report Type Research Report
Publication Date Jun 1, 2016
APA6 Citation Hunt, S. (2016). Continuation- Musical Note Prediction Through Analysis. UWE
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