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--- |
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license: cc-by-4.0 |
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task_categories: |
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- audio-classification |
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tags: |
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- audio |
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size_categories: |
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- 10K<n<100K |
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paperswithcode_id: audioset |
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dataset_info: |
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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 |
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num_examples: 18685 |
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- name: test |
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num_bytes: 23763682278 |
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num_examples: 17142 |
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download_size: 49805654900 |
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dataset_size: 49779893265 |
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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 Details |
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This repository contains the balanced training set and evaluation set of |
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the [AudioSet data]( |
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https://research.google.com/audioset/dataset/index.html). The YouTube |
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videos were downloaded in March 2023, so not all of the original audios |
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are available. |
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|
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The distribuion of audio clips is as follows. In parentheses is the dict |
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key used for HugginFace `datasets`: |
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- `bal_train` (`train`): 18685 audio clips out of 22160 originally. |
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- `eval` (`test`): 17142 audio clips out of 20371 originally. |
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|
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You can use the `datasets` library to load this dataset, in which case |
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the raw audio will be returned along with a sequence of one or more |
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labels. Note that the raw audio is returned without further processing, |
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so you will need to decode and possibly downsample the audio for model |
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training. |
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|
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Example instance from the `train` subset: |
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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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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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## 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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