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  1. README.md +18 -5
README.md CHANGED
@@ -15,8 +15,19 @@ tags:
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  size_categories:
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  - 10K<n<100K
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  configs:
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- - config_name: NonSpeech7k
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  default: true
 
 
 
 
 
 
 
 
 
 
 
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  data_files:
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  - split: train
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  path: "NonSpeech7k/train/*.tar"
@@ -50,7 +61,10 @@ A collection of human non-speech vocal sound datasets in WebDataset format, usef
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  ## Subsets
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- ### NonSpeech7k (default)
 
 
 
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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)
@@ -102,13 +116,12 @@ All datasets are stored in WebDataset format:
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  ```python
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  from datasets import load_dataset
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- # Load default subset (NonSpeech7k)
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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", "VocalSound")
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- ds = load_dataset("gijs/speech-utterances", "EmoGator")
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  # Access individual examples
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  print(ds['train'][0])
 
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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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  ## Subsets
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+ ### all (default)
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+ All datasets concatenated together (~75k samples total).
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+
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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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  ```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])