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--- |
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license: cc-by-nc-sa-4.0 |
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task_categories: |
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- audio-classification |
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language: |
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- en |
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- ko |
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- pt |
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tags: |
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- non-speech |
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- vocal-sounds |
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- emotion |
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- human-voice |
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- webdataset |
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size_categories: |
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- 10K<n<100K |
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configs: |
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- config_name: all |
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default: true |
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data_files: |
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- split: train |
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path: |
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- "NonSpeech7k/train/*.tar" |
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- "NonSpeech7k/test/*.tar" |
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- "VocalSound/*.tar" |
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- "DeeplyNonverbalVocalization/*.tar" |
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- "EmoGator/*.tar" |
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- "Expresso/*.tar" |
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- "VIVAE/*.tar" |
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- config_name: NonSpeech7k |
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data_files: |
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- split: train |
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path: "NonSpeech7k/train/*.tar" |
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- split: test |
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path: "NonSpeech7k/test/*.tar" |
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- config_name: VocalSound |
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data_files: |
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- split: train |
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path: "VocalSound/*.tar" |
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- config_name: DeeplyNonverbalVocalization |
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data_files: |
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- split: train |
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path: "DeeplyNonverbalVocalization/*.tar" |
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- config_name: EmoGator |
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data_files: |
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- split: train |
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path: "EmoGator/*.tar" |
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- config_name: Expresso |
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data_files: |
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- split: train |
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path: "Expresso/*.tar" |
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- config_name: VIVAE |
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data_files: |
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- split: train |
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path: "VIVAE/*.tar" |
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--- |
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# Speech Utterances Dataset Collection |
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A collection of human non-speech vocal sound datasets in WebDataset format, useful for audio classification tasks involving vocal expressions, emotions, and non-verbal sounds. |
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## Subsets |
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### all (default) |
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All datasets concatenated together (~75k samples total). |
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### NonSpeech7k |
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- **Samples**: 7,014 (train: 6,289, test: 725) |
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- **Classes**: Breathing, Coughing, Crying, Laughing, Screaming, Sneezing, Yawning |
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- **Source**: [Zenodo](https://zenodo.org/records/6967442) |
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- **License**: CC BY-NC-SA 4.0 |
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### VocalSound |
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- **Samples**: 21,024 |
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- **Classes**: Laughter, Sigh, Cough, Throat clearing, Sneeze, Sniff |
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- **Speakers**: 3,365 from 60 countries |
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- **Source**: [GitHub](https://github.com/YuanGongND/vocalsound) |
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- **License**: CC BY-SA 4.0 |
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### DeeplyNonverbalVocalization |
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- **Samples**: 726 (5% subset of full dataset) |
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- **Classes**: 16 (teeth-chattering, teeth-grinding, tongue-clicking, nose-blowing, coughing, yawning, throat-clearing, sighing, lip-popping, lip-smacking, panting, crying, laughing, sneezing, moaning, screaming) |
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- **Source**: [OpenSLR](https://www.openslr.org/99/) |
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- **License**: CC BY-NC-ND 4.0 |
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### EmoGator |
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- **Samples**: 32,130 |
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- **Classes**: 30 emotion categories (Adoration, Amusement, Anger, Awe, Confusion, Contempt, Contentment, Desire, Disappointment, Disgust, Distress, Ecstasy, Elation, Embarrassment, Fear, Guilt, Interest, Neutral, Pain, Pride, Realization, Relief, Romantic Love, Sadness, Serenity, Shame, Surprise Negative, Surprise Positive, Sympathy, Triumph) |
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- **Contributors**: 357 |
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- **Source**: [GitHub](https://github.com/fredbuhl/EmoGator) |
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- **License**: Apache 2.0 |
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### Expresso |
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- **Samples**: 12,293 |
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- **Styles**: 26 expressive styles (angry, animal, awe, bored, calm, child, confused, default, desire, disgusted, enunciated, fast, fearful, happy, laughing, narration, non_verbal, projected, sad, sarcastic, singing, sleepy, sympathetic, whisper, etc.) |
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- **Speakers**: 4 (2 male, 2 female) |
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- **Source**: [Expresso](https://speechbot.github.io/expresso) |
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- **License**: CC BY-NC 4.0 |
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### VIVAE |
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- **Samples**: 1,565 |
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- **Emotions**: achievement, anger, fear, pain, pleasure, surprise |
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- **Intensity levels**: low, moderate, strong, peak |
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- **Speakers**: 10 |
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- **Source**: [Zenodo](https://zenodo.org/record/4066235) |
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- **License**: CC BY 4.0 |
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## Format |
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All datasets are stored in WebDataset format: |
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- **Audio**: FLAC, 48kHz, 16-bit, mono |
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- **Metadata**: JSON with "text" key containing labels |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Load all datasets concatenated (default) |
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ds = load_dataset("gijs/speech-utterances") |
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# Load a specific subset |
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ds = load_dataset("gijs/speech-utterances", "Expresso") |
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ds = load_dataset("gijs/speech-utterances", "NonSpeech7k") |
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# Access individual examples |
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print(ds['train'][0]) |
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``` |
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## Citations |
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Please cite the original datasets when using this collection: |
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- **NonSpeech7k**: Rashid et al. (2023). Nonspeech7k dataset. IET Signal Processing. |
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- **VocalSound**: Gong et al. (2022). Vocalsound. ICASSP 2022. |
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- **DeeplyNonverbalVocalization**: Deeply Inc. Vocal Characterizer Dataset. |
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- **EmoGator**: Buhl et al. (2023). arXiv:2301.00508 |
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- **Expresso**: Nguyen et al. (2023). EXPRESSO. INTERSPEECH 2023. |
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- **VIVAE**: Holz et al. (2020). VIVAE corpus. Zenodo. |
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