Published July 31, 2020
| Version 1.0
Dataset
Open
Schubert Winterreise Dataset
Creators
- 1. International Audio Laboratories Erlangen
- 2. Utrecht University
- 3. Blue Square Group e.V., Bonn
Description
The Schubert Winterreise Dataset (SWD) is a multimodal dataset comprising various representations and annotations of Franz Schubert's 24-song cycle Winterreise. The primary material (raw data) consists of textual representations of the songs' lyrics, music scores in image, symbolic, and MIDI format, as well as nine audio recordings of performances (only two included due to copyright issues). The secondary material (annotations) comprises information of musical measure positions in sheet music images and audio recordings as well as analyses of chords, local keys, global keys, and structural parts. The SWD is organized as follows:
01_RawData
- lyrics_txt
- score-IMSLP_png
- score-IMSLP_pdf-complete.pdf
- score_sibelius
- score_pdf
- score_musicxml
- score_midi
- audio_wav
02_Annotations
- ann_score-IMSLP_measure
- ann_score_chord
- ann_score_localkey-ann1
- ann_score_localkey-ann2
- ann_score_localkey-ann3
- ann_score_globalkey.csv
- ann_score_structure
- ann_audio_measure
- ann_audio_chord
- ann_audio_localkey-ann1
- ann_audio_localkey-ann2
- ann_audio_localkey-ann3
- ann_audio_globalkey.csv
- ann_audio_structure
03_ExtraMaterial
- original data, scripts for cutting, licenses, ...
Notes
For a detailed description, please see the accompanying journal paper:
Christof Weiß, Frank Zalkow, Vlora Arifi-Müller, Meinard Müller, Hendrik Vincent Koops, Anja Volk, and Harald G. Grohganz. Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis. In: ACM Journal on Computing and Cultural Heritage, XX:YY, 2020, under revision
Files
Schubert_Winterreise_Dataset_v1-0.zip
Files
(505.7 MB)
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Additional details
References
- Frans Absil. Musical Analysis – Visiting the Great Composers (6th ed.), 2017
- Harald Grohganz. Algorithmen zur strukturellen Analyse von Musikaufnahmen. Ph.D. Dissertation. University of Bonn, Germany, 2015
- Hendrik Vincent Koops. Computational Modelling of Variance in Musical Harmony. Ph.D. Dissertation. Utrecht University, Utrecht, The Netherlands, 2019
- Frank Zalkow, Angel Villar Corrales, TJ Tsai, Vlora Arifi-Müller, and Meinard Müller. Tools for Semi-Automatic Bounding Box Annotation of Musical Measures in Sheet Music. In Demos and Late Breaking News of the International Society for Music Information Retrieval Conference (ISMIR). Delft, The Netherlands, 2019