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--- |
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language: |
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- en |
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license: cc-by-4.0 |
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size_categories: |
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- 10K<n<100K |
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- 1M<n<10M |
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source_datasets: |
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- original |
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task_categories: |
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- audio-classification |
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paperswithcode_id: audioset |
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pretty_name: AudioSet |
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config_names: |
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- balanced |
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- unbalanced |
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tags: |
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- audio |
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dataset_info: |
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- config_name: balanced |
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features: |
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- name: video_id |
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dtype: string |
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- name: audio |
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dtype: audio |
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- name: labels |
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sequence: string |
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- name: human_labels |
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sequence: string |
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splits: |
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- name: train |
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num_bytes: 26016210987 |
|
num_examples: 18685 |
|
- name: test |
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num_bytes: 23763682278 |
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num_examples: 17142 |
|
download_size: 49805654900 |
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dataset_size: 49779893265 |
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- config_name: unbalanced |
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features: |
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- name: video_id |
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dtype: string |
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- name: audio |
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dtype: audio |
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- name: labels |
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sequence: string |
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- name: human_labels |
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sequence: string |
|
splits: |
|
- name: train |
|
num_bytes: 2408656417541 |
|
num_examples: 1738788 |
|
- name: test |
|
num_bytes: 23763682278 |
|
num_examples: 17142 |
|
download_size: 2433673104977 |
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dataset_size: 2432420099819 |
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--- |
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|
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# Dataset Card for AudioSet |
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|
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## Dataset Description |
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- **Homepage**: https://research.google.com/audioset/index.html |
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- **Paper**: https://storage.googleapis.com/gweb-research2023-media/pubtools/pdf/45857.pdf |
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- **Leaderboard**: https://paperswithcode.com/sota/audio-classification-on-audioset |
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|
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### Dataset Summary |
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[AudioSet](https://research.google.com/audioset/dataset/index.html) is a |
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dataset of 10-second clips from YouTube, annotated into one or more |
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sound categories, following the AudioSet ontology. |
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|
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### Supported Tasks and Leaderboards |
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- `audio-classification`: Classify audio clips into categories. The |
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leaderboard is available |
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[here](https://paperswithcode.com/sota/audio-classification-on-audioset) |
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### Languages |
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The class labels in the dataset are in English. |
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## Dataset Structure |
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### Data Instances |
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Example instance from the dataset: |
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```python |
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{ |
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'video_id': '--PJHxphWEs', |
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'audio': { |
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'path': 'audio/bal_train/--PJHxphWEs.flac', |
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'array': array([-0.04364824, -0.05268681, -0.0568949 , ..., 0.11446512, |
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0.14912748, 0.13409865]), |
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'sampling_rate': 48000 |
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}, |
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'labels': ['/m/09x0r', '/t/dd00088'], |
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'human_labels': ['Speech', 'Gush'] |
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} |
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``` |
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|
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### Data Fields |
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Instances have the following fields: |
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- `video_id`: a `string` feature containing the original YouTube ID. |
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- `audio`: an `Audio` feature containing the audio data and sample rate. |
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- `labels`: a sequence of `string` features containing the labels |
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associated with the audio clip. |
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- `human_labels`: a sequence of `string` features containing the |
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human-readable forms of the same labels as in `labels`. |
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|
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### Data Splits |
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The distribuion of audio clips is as follows: |
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|
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#### `balanced` configuration |
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| |train|test | |
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|-----------|----:|----:| |
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|# instances|18685|17142| |
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|
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#### `unbalanced` configuration |
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| |train |test | |
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|-----------|------:|----:| |
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|# instances|1738788|17142| |
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|
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## Dataset Creation |
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|
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### Curation Rationale |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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### Source Data |
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|
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#### Initial Data Collection and Normalization |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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#### Who are the source language producers? |
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The labels are from the AudioSet ontology. Audio clips are from YouTube. |
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|
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### Annotations |
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|
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#### Annotation process |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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#### Who are the annotators? |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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### Personal and Sensitive Information |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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## Considerations for Using the Data |
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|
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### Social Impact of Dataset |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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### Discussion of Biases |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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### Other Known Limitations |
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1. The YouTube videos in this copy of AudioSet were downloaded in March |
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2023, so not all of the original audios are available. The number of |
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clips able to be downloaded is as follows: |
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- Balanced train: 18685 audio clips out of 22160 originally. |
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- Unbalanced train: 1738788 clips out of 2041789 originally. |
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- Evaluation: 17142 audio clips out of 20371 originally. |
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2. Most audio is sampled at 48 kHz 24 bit, but about 10% is sampled at |
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44.1 kHz 24 bit. Audio files are stored in the FLAC format. |
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|
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## Additional Information |
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|
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### Dataset Curators |
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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### Licensing Information |
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The AudioSet data is licensed under CC-BY-4.0 |
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## Citation |
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```bibtex |
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@inproceedings{jort_audioset_2017, |
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title = {Audio Set: An ontology and human-labeled dataset for audio events}, |
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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}, |
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year = {2017}, |
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booktitle = {Proc. IEEE ICASSP 2017}, |
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address = {New Orleans, LA} |
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} |
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``` |
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