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Dataset . 2026
License: CC BY NC SA
Data sources: Datacite
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Dataset . 2026
License: CC BY NC SA
Data sources: Datacite
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Beethoven Symphony Excerpt Dataset (BSED): An Evaluation Dataset for Orchestral Music Transcription

Authors: Berendes, Hans-Ulrich; Saha, Abhirup; Maman, Ben; Arifi-Müller, Vlora; Müller, Meinard;

Beethoven Symphony Excerpt Dataset (BSED): An Evaluation Dataset for Orchestral Music Transcription

Abstract

The Beethoven Symphony Excerpt Dataset (BSED) is a dataset primarily designed to support the evaluation of Automatic Music Transcription (AMT) for orchestral music. The accompanying Beethoven Symphony Dataset (BSD) serves as a larger training dataset. While primarily developed for AMT, both datasets can also be used for a range of Music Information Retrieval (MIR) tasks involving orchestral music, such as score-audio alignment and music synthesis. BSED The BSED comprises 20 score excerpts from Beethoven's symphonies. For each excerpt, we provide five synchronized audio versions: four real concert recordings and one synthetic rendition. The corresponding symbolic scores are available in MusicXML, Sibelius, MIDI, and CSV note-event formats. We obtain note-level annotations for each audio recording by aligning the symbolic scores to the audio using a robust score-audio alignment pipeline, followed by manual verification and refinement to ensure high temporal accuracy. BSD The BSD comprises public-domain audio recordings of Beethoven's complete symphonies, totaling approximately 62 hours of audio material. As with the BSED, note-level annotations are obtained by aligning symbolic scores to the audio recordings. However, due to the considerably larger scale of the dataset, the alignments have not undergone the same level of manual verification as those in the BSED. Consequently, the BSD serves as a valuable large-scale training resource, offering substantial diversity in performances while providing slightly less rigorously validated annotations than the BSED. For more information and tools to recreate and interact with the data, please have a look at the accompanying GitHub repository.If you find any errors or problems with the dataset, please raise an issue in the GitHub repository. A demo of the dataset can be found here: https://audiolabs-erlangen.de/resources/MIR/2026-BSED-BSD Please cite the following paper if you use our work: Berendes, H.-U., Saha, A., Maman, B., Arifi-Müller, V., & Müller, M. (2026). Beethoven Symphony Excerpt Dataset (BSED): An Evaluation Dataset for Orchestral Music Transcription. Transactions of the International Society for Music Information Retrieval, 9(1), 405–422. DOI: https://doi.org/10.5334/tismir.343

Keywords

Music Information Retrieval, Beethoven Symphonies, Automatic Music Transcription, Orchestra, Score-Audio Alignment

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average