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This repository contains the annotations and download scripts for the audio files of the GiantSteps Tempo data set. This data set was published at ISMIR 2015: P. Knees et al.: "Two data sets for tempo estimation and key detection in electronic dance music annotated from user corrections"

GiantSteps/giantsteps-tempo-dataset

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name:             GiantSteps (tempo+genre)

contact:          Richard Vogl <richard.vogl@tuwien.ac.at>
                  Peter Knees <peter.knees@tuwien.ac.at>

description:      collection of annotations for 664 2min(1) audio previews from
                  www.beatport.com

references:       [1] Peter Knees, Ángel Faraldo, Perfecto Herrera, Richard Vogl,
                  Sebastian Böck, Florian Hörschläger, Mickael Le Goff: "Two data
                  sets for tempo estimation and key detection in electronic dance
                  music annotated from user corrections", Proc. of the 16th
                  Conference of the International Society for Music Information
                  Retrieval (ISMIR'15), Oct. 2015, Malaga, Spain.

                  [2] Hendrik Schreiber, Meinard Müller: "A Crowdsourced Experiment
                  for Tempo Estimation of Electronic Dance Music", Proc. of the
                  19th Conference of the International Society for Music
                  Information Retrieval (ISMIR'18), Sept. 2018, Paris, France.

annotations:      tempo (bpm), genre

content:
=========================================================================
audio/                   original audio files in mp3 format
md5/                     md5 hashes of original audio files
annotations/             annotations from [1]
annotations/genre/       genre annotations
annotations/tempo/       tempo annotations
annotations/giantsteps/  annotations in the GiantSteps project format
annotations/jams/        annotations in the JAMS (https://github.com/marl/jams) format
annotations_v2/          annotations from [2]
annotations_v2/tempo/    tempo annotations
annotations_v2/jams/     annotations in the JAMS (https://github.com/marl/jams) format
annotations_v2/mirex/    annotations in MIREX-style, i.e. (T1 T2 ST1)
splits/                  file splitting definitions

notes:
=========================================================================
The audio files (664 files, size ~1gb) can be downloaded from http://www.beatport.com/
using the bash script:

./audio_dl.sh

To download the files manually use links of the following form:
http://geo-samples.beatport.com/lofi/<name of mp3 file>
e.g.:
http://geo-samples.beatport.com/lofi/5377710.LOFI.mp3

To convert the audio files to .wav use (bash + sox):

./convert_audio.sh

To retrieve the genre information, the JSON contained within the website was parsed.
The tempo annotation was extracted from forum entries of people correcting the bpm values (i.e. manual annotation of tempo).
For more information please contact creators.

[2] found some files without tempo. There are:

3041381.LOFI.mp3
3041383.LOFI.mp3
1327052.LOFI.mp3

Their v2 tempo is denoted as 0.0 in tempo and mirex and has no annotation in the JAMS format.

(1): Most of the audio files are 120 seconds long. Exceptions are:
name              length
906760.LOFI.mp3   62
1327052.LOFI.mp3  70
4416506.LOFI.mp3  80
1855660.LOFI.mp3  119
3419452.LOFI.mp3  119
3577631.LOFI.mp3  119

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This repository contains the annotations and download scripts for the audio files of the GiantSteps Tempo data set. This data set was published at ISMIR 2015: P. Knees et al.: "Two data sets for tempo estimation and key detection in electronic dance music annotated from user corrections"

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