README.md

metadata

task_categories:
  - audio-classification
language:
  - en
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: scream_type
      dtype: string
    - name: song_name
      dtype: string
    - name: band_name
      dtype: string
    - name: album_name
      dtype: string
    - name: release_year
      dtype: int64
    - name: video_id
      dtype: string
    - name: timestamp_start
      dtype: float64
    - name: timestamp_end
      dtype: float64
    - name: sample_rate
      dtype: int64
  splits:
    - name: train
      num_bytes: 114577942.825
      num_examples: 1575
  download_size: 119156239
  dataset_size: 114577942.825

Dataset card for Scream Detection in Heavy Metal Music

This dataset contains the processed dataset used in the paper "Scream Detection in Heavy Metal Music" (Kalbag & Lerch, 2022) from the Georgia Institute of Technology.

Kalbag, V., & Lerch, A. (2022). Scream detection in heavy metal music. arXiv preprint arXiv:2205.05580.

Data Fields

• audio: the trimmed audio file from the song.
• scream_type: the target variable for classification i.e. layered, lowfry, highfry, midfry, clean.
• band_name: the name of the artist performing the song.
• album_name: the name of the album where the song was released.
• song_name: the name of the song.
• release_year: the release year of the song.
• timestamp_start: the start time of the snippet from the full audio.
• tiemstamp_end: the end time of the snippet from the full audio.
• sample_rate: the sampling rate of the audio.