---
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.