The Batik-plays-Mozart Corpus: Linking Performance to Score to Musicological Annotations
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Abstract (arXiv)
We present the Batik-plays-Mozart Corpus, a piano performance dataset combining professional Mozart piano sonata performances with expert-labelled scores at a note-precise level. The performances originate from a recording by Viennese pianist Roland Batik on a computer-monitored B"osendorfer grand piano, and are available both as MIDI files and audio recordings. They have been precisely aligned, note by note, with a current standard edition of the corresponding scores (the New Mozart Edition) in such a way that they can further be connected to the musicological annotations (harmony, cadences, phrases) on these scores that were recently published by Hentschel et al. (2021). The result is a high-quality, high-precision corpus mapping scores and musical structure annotations to precise note-level professional performance information. As the first of its kind, it can serve as a valuable resource for studying various facets of expressive performance and their relationship with structural aspects. In the paper, we outline the curation process of the alignment and conduct two exploratory experiments to demonstrate its usefulness in analyzing expressive performance.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Sep 2023.
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Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024Controlling Surprisal in Music Generation via Information Content Curve Matchingcited by 7
- 2025The GigaMIDI Dataset with Features for Expressive Music Performance Detectioncited by 7
- 2024TheGlueNote: Learned Representations for Robust and Flexible Note Alignmentcited by 1
- 2026PianoCoRe: Combined and Refined Piano MIDI Datasetcited by 1
- 2026PianoCoRe: Combined and Refined Piano MIDI Dataset7 May 2026
- 2025The GigaMIDI Dataset with Features for Expressive Music Performance Detection24 Feb 2025
- 2024Controlling Surprisal in Music Generation via Information Content Curve Matching12 Aug 2024
- 2024TheGlueNote: Learned Representations for Robust and Flexible Note Alignment8 Aug 2024