DOI: 10.5281/zenodo.12783403
title: BPSD: A Coherent Multi-Version Dataset for Analyzing the First Movements of Beethoven's Piano Sonatas

description: -- Full paper: https://doi.org/10.5334/tismir.196 --

This repository contains the Beethoven Piano Sonata Dataset (BPSD), a multi-version dataset focusing on the first movements of Beethoven's 32 piano sonatas. Recognized as pivotal works in classical music, Beethoven's piano sonatas have profoundly shaped Western classical music, holding a significant place in cultural history.The BPSD includes sheet music in different machine-readable formats and audio recordings from eleven performances, with four of them being in the public domain and freely accessible for research purposes. A key feature of BPSD is its coherence, ensuring alignment of all versions on a unified musical timeline and enforcing consistent structures through careful editing of both score and audio representations.The focus and main motivation for the design choices made in BPSD are on the technical and computational level. In particular, BPSD facilitates the assessment of algorithmic approaches in tasks like harmony analysis, structure analysis, music transcription, beat and downbeat estimation, and score following. The dataset's coherence makes it an ideal platform for systematically training and evaluating deep learning methods, shedding light on their robustness and uncovering data biases across different data splits using cross-version strategies for evaluation. To ease applicability for computational approaches, the BPSD is based on various simplifications that may be disputable from a musicological perspective. Rather than providing novel musicological annotations, the main conceptual contribution of BPSD with its measure annotations is to provide a framework for transferring existing annotations from the symbolic to the audio domain. We hope that, as such, BPSD is also useful for the systematic analysis and exploration of Beethoven's piano sonatas, providing insights into their influence on the development of harmony and structure in Western classical music. Beyond research applications, the dataset also holds educational potential, aiding in the preparation and presentation of Beethoven's work to a broader audience through interactive multimedia experiences.
description: - 0_RawData

Raw audio and symbolic data


| - audio_ripped
Audio files as ripped from the CD. Important: these raw audio files are not contained in the .zip archive, as they do not correspond to the annotations (due to, e.g., additional or missing repeats). The audio corresponding to the annotations is stored in 1_Audio. 


| - score_pdf_scan
Scanned score from IMSLP


| - score_pdf_repetitions
Symbolic score in PDF format with repeat signs


| - score_pdf_unfolded
Symbolic score in PDF format with unfolded repetitions


| - score_sibelius_repetitions
Symbolic score in Sibelius format with repeat signs


| - score_sibelius_unfolded
Symbolic score in Sibelius format with unfolded repetitions


| - score_xml_repetitions
Symbolic score in MusicXML format with repeat signs


| - score_xml_unfolded
Symbolic score in MusicXML format with unfolded repetitions


| - score_midi
MIDI export of the symbolic score


- 1_Audio
Audio files with coherent structure that correspond to the annotations


- 2_Annotations
Annotations with musical and physical timelines


| - ann_score_note
Note events with start and end given in musical time


| - ann_score_chord
Harmony annotations given in musical time


| - ann_score_localkey
Local key annotations given in musical time


| - ann_score_globalkey
Global key annotations


| - ann_score_structureFine
Fine structure annotations given in musical time


| - ann_score_structureCoarse
Coarse structure annotations given in musical time


| - ann_audio_note
Note events with start and end given in physical time


| - ann_audio_midi
Note events in physical time in MIDI format


| - ann_audio_beat
Beat annotations given in physical time


| - ann_audio_measure
Measure annotations given in physical time


| - ann_audio_startEnd
Start and end of audio recordings (for removing silence/applause) given in physical time


| - ann_audio_syncInfo
Alignment tuples for converting between musical and physical timeline


| - ann_audio_modifications
Annotations for structural modifications of recordings


| - ann_audio_chord
Harmony annotations given in physical time


| - ann_audio_localkey
Local key annotations given in physical time


| - ann_audio_structureFine
Fine structure annotations given in physical time


| - ann_audio_structureCoarse
Coarse structure annotations given in physical time


- 3_Scripts
Python scripts to convert raw data into the structured format. Maintained code is available on GitHub
description: Audio Versions




ID
Performer
Recording Year
Label
Release year
EAN code
MusicBrainz ReleaseID


AS35
Artur Schnabel
1935
Warner Classics
2016
0190295975050
7bd7338c-2acc-49f4-b262-122085a3e694


FG58
Friedrich Gulda
1958
Decca
1958
028948514519
n.a.


FJ62
Fritz Jank
1962
Instituto Piano Brasileiro
2021
n.a.
available at IMSLP


WK64
Wilhelm Kempff
1964
Deutsche Grammophon
1995
028944796629
38864449-d1e9-4b4f-b5a6-e73acc954e27


FG67
Friedrich Gulda
1967
Amadeo/Decca
1968
028947687610
83f869ea-fc64-4fe9-b424-52d4282f706f


VA81
Vladimir Ashkenazy
1981
London Records
1995
028944370621
36fcb34f-59ab-3e4d-a066-3067ed82ed33


DB84
Daniel Barenboim
1984
Deutsche Grammophon
1984
028941375926, 028941376626
261a38ba-9c56-458e-9a4d-c7b6b4acb3a3, b4b49c3d-f86a-4701-b967-d4e726ab8ef0


JJ90
Jeno Jando
1990
NAXOS
1990
730099150224
2f94e0a3-be66-4894-9c9d-83d5890081da


AB96
Alfred Brendel
1996
Philips
1996
028941257529
6f419224-c6fb-4c38-871e-5799b755a387


MB97
Malcolm Bilson et al.
1997
Claves
1997
7619931970721
718bac94-7c2c-48ea-8f30-dc230aab019d


MC22
Muriel Chemin
2022
Odradek
2022
855317003615
n.a.
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the project "Computational Analysis of Harmonic Structures" under No. 252013209 (MU 2686/7-2), the project "Learning with Music Signals: Technology Meets Education" under No. 500643750 (MU 2686/15-1), and the Emmy Noether research group "Computational Analysis of Music Audio Recordings: A Cross-Version Approach" under No. 531250483 (WE 6611/3-1). We express our gratitude to all team members, student assistants, and colleagues who played pivotal roles in the data curation process and annotation work. Special mentions among the numerous contributors include Harald Grohganz, Celina Hüttner, Nanzhu Jiang, and Michael Kohl. The International Audio Laboratories Erlangen are a joint institution of the Friedrich-Alexander-Universität Erlangen-Nüurnberg (FAU) and Fraunhofer Institute for Integrated Circuits IIS.
description: Known Problems



Cadenza missing in Op002No3-01



The cadenza in Op002No3-01, measure 322, is not included in the sibelius files, XML files, MIDI files, ann_score_note, and ann_audio_note



Missing measures in Op057-01_FJ62



Jank's recording deviates from the notated score in Op057-01, starting at measure 86.5 and continuing for 2 more measures. He then directly jumps to measure 93, where the playing is correct again. In summary, 2 measures deviate from the score and 4.5 measures are missing completely.