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Datasets:
gijs
/
speech-utterances

Tasks:
Audio Classification
Modalities:
Audio
Text
Formats:
webdataset
Languages:
English
Korean
Portuguese
Size:
100K - 1M
ArXiv:
Tags:
non-speech
vocal-sounds
emotion
human-voice
webdataset
Libraries:
Datasets
WebDataset
License:
Dataset card Data Studio Files
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  1. EmoGator/0001.tar +3 -0
  2. EmoGator/0002.tar +3 -0
  3. EmoGator/0003.tar +3 -0
  4. EmoGator/0004.tar +3 -0
  5. EmoGator/0005.tar +3 -0
  6. EmoGator/0006.tar +3 -0
  7. EmoGator/0007.tar +3 -0
  8. EmoGator/0008.tar +3 -0
  9. EmoGator/0009.tar +3 -0
  10. EmoGator/0010.tar +3 -0
  11. EmoGator/0011.tar +3 -0
  12. EmoGator/0012.tar +3 -0
  13. EmoGator/0013.tar +3 -0
  14. EmoGator/0014.tar +3 -0
  15. EmoGator/0015.tar +3 -0
  16. EmoGator/0016.tar +3 -0
  17. EmoGator/0017.tar +3 -0
  18. EmoGator/0018.tar +3 -0
  19. EmoGator/0019.tar +3 -0
  20. EmoGator/0020.tar +3 -0
  21. EmoGator/0021.tar +3 -0
  22. EmoGator/0022.tar +3 -0
  23. EmoGator/0023.tar +3 -0
  24. EmoGator/0024.tar +3 -0
  25. EmoGator/0025.tar +3 -0
  26. EmoGator/0026.tar +3 -0
  27. EmoGator/0027.tar +3 -0
  28. EmoGator/0028.tar +3 -0
  29. EmoGator/0029.tar +3 -0
  30. EmoGator/0030.tar +3 -0
  31. EmoGator/0031.tar +3 -0
  32. EmoGator/0032.tar +3 -0
  33. EmoGator/0033.tar +3 -0
  34. EmoGator/info.md +22 -0
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+ # EmoGator Dataset
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+
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+ **Source:** https://github.com/fredbuhl/EmoGator
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+
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+ **License:** Apache 2.0
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+
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+ **Description:** The EmoGator dataset consists of 32,130 non-speech vocal bursts (for example: laughter, sighs, moans, and groans) in 30 emotion categories. The dataset contains 357 contributors, 30 vocal burst categories, and 3 instances of each category per contributor, providing a balanced dataset with 90 samples per contributor.
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+
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+ **Emotion Categories (30):**
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+ - Adoration, Amusement, Anger, Awe, Confusion
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+ - Contempt, Contentment, Desire, Disappointment, Disgust
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+ - Distress, Ecstasy, Elation, Embarrassment, Fear
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+ - Guilt, Interest, Neutral, Pain, Pride
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+ - Realization, Relief, Romantic Love, Sadness, Serenity
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+ - Shame, Surprise (Negative), Surprise (Positive), Sympathy, Triumph
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+
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+ **Format:** FLAC 48kHz 16-bit mono
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+
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+ **Total samples:** 32130
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+ **Total tar files:** 33
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+
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+ **Reference:** https://arxiv.org/abs/2301.00508