README.md

metadata

license: mit
size_categories:
  - 1K<n<10K
pretty_name: EDM CUE
dataset_info:
  features:
    - name: id
      dtype: int64
    - name: title
      dtype: string
    - name: artists
      dtype: string
    - name: duration
      dtype: int64
    - name: genre
      sequence: string
    - name: key
      sequence: string
    - name: beat_grid
      struct:
        - name: bpm
          dtype: float64
        - name: init_beat
          dtype: int64
        - name: start_pos
          dtype: float64
        - name: time_sig
          dtype: string
    - name: cue_pts
      sequence: float64
  splits:
    - name: train
      num_bytes: 690103
      num_examples: 4609
    - name: valid
      num_bytes: 16842
      num_examples: 101
  download_size: 292711
  dataset_size: 706945
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: valid
        path: data/valid-*
tags:
  - music

What is EDM-CUE?

The EDM-CUE dataset contains metadata for ~5k EDM tracks, most importantly cue points manually placed by human experts.

For more information see our ISMIR'24 paper Cue Point Estimation using Object Detection [link coming soon].

Dataset Structure

The dataset contains the following features:

• id: Track ID on Deezer.
• title: Track name.
• artists: Track artists.
• duration: Track duration in seconds.
• genre: List of genres (possibly incomplete).
• key: Alphanumeric key of the track generated by rekordbox (possibly incorrect).
• beat_grid: Contains 4 values to compute the grid. 'start_pos' is the starting position in seconds, 'init_beat' is the beat count of 'start_pos', 'bpm' is the beats per minute tempo, and 'time_sig' is the time signature in string format.
• cue_pts: Cue point position in seconds.