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
license: mit
tags:
- music
size_categories:
- 1K<n<10K
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.