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Bach or Mock? A Grading Function for Chorales in the Style of JS Bach

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Document pages: 3 pages

Abstract: Deep generative systems that learn probabilistic models from a corpus ofexisting music do not explicitly encode knowledge of a musical style, comparedto traditional rule-based systems. Thus, it can be difficult to determinewhether deep models generate stylistically correct output without expertevaluation, but this is expensive and time-consuming. Therefore, there is aneed for automatic, interpretable, and musically-motivated evaluation measuresof generated music. In this paper, we introduce a grading function thatevaluates four-part chorales in the style of J.S. Bach along important musicalfeatures. We use the grading function to evaluate the output of a Transformermodel, and show that the function is both interpretable and outperforms humanexperts at discriminating Bach chorales from model-generated ones.

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