| | --- |
| | dataset_info: |
| | features: |
| | - name: ID |
| | dtype: string |
| | - name: audio |
| | dtype: |
| | audio: |
| | sampling_rate: 16000 |
| | - name: country |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 1783821218.4609375 |
| | num_examples: 12900 |
| | - name: validation |
| | num_bytes: 1746232603.9765625 |
| | num_examples: 12700 |
| | download_size: 3533048242 |
| | dataset_size: 3530053822.4375 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | - split: validation |
| | path: data/validation-* |
| | --- |
| | |
| |
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| | To participate in the NADI 2025 Spoken Dialect ID challenge please make sure you have visited the main NADI 2025 page [link](https://nadi.dlnlp.ai/2025/), and sign the participation form on CodaBench. Ensure your email + contact information matches your Huggingface Access request email. |
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| | This is the `adaptation' split for the NADI 2025 Spoken Dialect ID task. As an adaptation split, the idea is to use an existing external dataset (e.g. ADI-17) for the main training, and then use this split for fine-tuning ('train') and validation. |
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| | This is a version of the nadi-asr dataset, without overlapping speakers between train / validation, and reformatted for ease of use in training for dialect ID. |
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