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The Rach3 Dataset: Towards Data-Driven Analysis of Piano Performance Rehearsal

  • Carlos Eduardo Cancino-Chacón,
  • Ivan Pilkov

摘要

Musicians spend more time practicing than performing live, but the process of rehearsal has been understudied. This paper introduces a dataset for using AI and machine learning to address this gap. The project observes the progression of pianists learning new repertoire over long periods of time by recording their rehearsals, generating a comprehensive multimodal dataset, the Rach3 dataset, with video, audio, and MIDI for computational analysis. This dataset will help investigating the way in which advanced students and professional classical musicians, particularly pianists, learn new music and develop their own expressive interpretations of a piece.