AudioSet / README.md
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metadata
license: cc-by-4.0
task_categories:
  - audio-classification
tags:
  - audio
size_categories:
  - 10K<n<100K
paperswithcode_id: audioset
dataset_info:
  features:
    - name: video_id
      dtype: string
    - name: audio
      dtype: audio
    - name: labels
      sequence: string
    - name: human_labels
      sequence: string
  splits:
    - name: train
      num_bytes: 26016210987
      num_examples: 18685
    - name: test
      num_bytes: 23763682278
      num_examples: 17142
  download_size: 49805654900
  dataset_size: 49779893265

Dataset Card for AudioSet

Dataset Details

This repository contains the balanced training set and evaluation set of the AudioSet data. The YouTube videos were downloaded in March 2023, so not all of the original audios are available.

The distribuion of audio clips is as follows. In parentheses is the dict key used for HugginFace datasets:

  • bal_train (train): 18685 audio clips out of 22160 originally.
  • eval (test): 17142 audio clips out of 20371 originally.

You can use the datasets library to load this dataset, in which case the raw audio will be returned along with a sequence of one or more labels. Note that the raw audio is returned without further processing, so you will need to decode and possibly downsample the audio for model training.

Example instance from the train subset:

{
 'video_id': '--PJHxphWEs',
 'audio': {
  'path': 'audio/bal_train/--PJHxphWEs.flac',
  'array': array([-0.04364824, -0.05268681, -0.0568949 , ...,  0.11446512,
          0.14912748,  0.13409865]),
  'sampling_rate': 48000
 },
 'labels': ['/m/09x0r', '/t/dd00088'],
 'human_labels': ['Speech', 'Gush']
}

Most audio is sampled at 48 kHz 24 bit, but about 10% is sampled at 44.1 kHz 24 bit. Audio files are stored in the FLAC format.

Citation

@inproceedings{jort_audioset_2017,
    title	= {Audio Set: An ontology and human-labeled dataset for audio events},
    author	= {Jort F. Gemmeke and Daniel P. W. Ellis and Dylan Freedman and Aren Jansen and Wade Lawrence and R. Channing Moore and Manoj Plakal and Marvin Ritter},
    year	= {2017},
    booktitle	= {Proc. IEEE ICASSP 2017},
    address	= {New Orleans, LA}
}