Datasets:
Update dataset descriptions
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README.md
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path: data/validation-*
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- split: test
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path: data/test-*
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---
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path: data/validation-*
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- split: test
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path: data/test-*
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task_categories:
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- automatic-speech-recognition
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tags:
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- paralinguistic
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pretty_name: a
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size_categories:
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- 100K<n<1M
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---
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A preprocessed version of `Switchboard Corpus`. The corpus audio has been upsampled to 16kHz, separated channels and the transcripts have been processed
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with special treats for paralinguistic events, particularly laughter and speech-laughs.
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This preprocessed dataset has been processed for ASR task. For the original dataset, please check out the original link: https://catalog.ldc.upenn.edu/LDC97S62
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The dataset has been splitted into train, test and validation sets with 70/20/10 ratio, as following summary:
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```python
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Train Dataset (70%): Dataset({
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features: ['audio', 'sampling_rate', 'transcript'],
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num_rows: 185402
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})
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Validation Dataset (10%): Dataset({
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features: ['audio', 'sampling_rate', 'transcript'],
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num_rows: 20601
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})
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Test Dataset (20%): Dataset({
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features: ['audio', 'sampling_rate', 'transcript'],
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num_rows: 51501
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})
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```
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An example of the content is this dataset:
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```
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```
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Regarding the total amount of laughter and speech-laugh existing in the dataset, here is the overview:
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```bash
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Train Dataset (swb_train): {'laughter': 16044, 'speechlaugh': 9586}
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Validation Dataset (swb_val): {'laughter': 1845, 'speechlaugh': 1133}
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Test Dataset (swb_test): {'laughter': 4335, 'speechlaugh': 2775}
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```
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