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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annotations added jams format annotations Nov 4, 2015
md5
splits
.gitignore
README
audio_dl.sh
convert_audio.sh

README

name:             GiantSteps (tempo+genre)

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

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

reference:        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.

annotations:      tempo (bpm), genre

content:
=========================================================================
audio/                   original audio files in mp3 format
md5/                     md5 hashes of original audio files
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
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.

(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