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mesolitica/Zeroshot-Audio-Classification-Instructions

Zeroshot-Audio-Classification-Instructions Convert audio classification dataset into zero-shot format speech instructions, support both single label and multi-label, VGGSound FSD50k Nonspeech7k urbansound8K VocalSound Emotion Gender ESD Emotion Age Language TAU Urban Acoustic Scenes 2022 CochlScene BirdCLEF_2021 EmoBox AudioSet We also converted huge WAV files into MP3 16k sample rate to reduce storage size. To prevent leakage, please do not include test set in training… See the full description on the dataset page: https://huggingface.co/datasets/mesolitica/Zeroshot-Audio-Classification-Instructions.

sourceHugging Faceupdated 1y agoView on Hugging Face
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Zeroshot-Audio-Classification-Instructions

Convert audio classification dataset into zero-shot format speech instructions, support both single label and multi-label,

  1. 1.VGGSound
  2. 2.FSD50k
  3. 3.Nonspeech7k
  4. 4.urbansound8K
  5. 5.VocalSound
  6. 6.Emotion
  7. 7.Gender
  8. 8.ESD Emotion
  9. 9.Age
  10. 10.Language
  11. 11.TAU Urban Acoustic Scenes 2022
  12. 12.CochlScene
  13. 13.BirdCLEF_2021
  14. 14.EmoBox
  15. 15.AudioSet

We also converted huge WAV files into MP3 16k sample rate to reduce storage size.

To prevent leakage, please do not include test set in training session.

how to prepare the dataset

bash
huggingface-cli download \
mesolitica/Zeroshot-Audio-Classification-Instructions \
--include "*.zip" \
--repo-type "dataset" \
--local-dir './'

huggingface-cli download \
mesolitica/Audio-Adversarial-Instructions \
--include "*.zip" \
--repo-type "dataset" \
--local-dir './'

huggingface-cli download \
mesolitica/Animal-Sound-Instructions \
--include "*.zip" \
--repo-type "dataset" \
--local-dir './'

huggingface-cli download \
mesolitica/EmoBox \
--include "*.zip" \
--repo-type "dataset" \
--local-dir './'

wget https://gist.githubusercontent.com/huseinzol05/2e26de4f3b29d99e993b349864ab6c10/raw/9b2251f3ff958770215d70c8d82d311f82791b78/unzip.py
python3 unzip.py

Acknowledgement

Special thanks to https://www.sns.com.my and Nvidia for 8x H100 node!