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--- |
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dataset_info: |
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features: |
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- name: ID |
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dtype: string |
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- name: audio |
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dtype: |
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audio: |
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sampling_rate: 16000 |
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- name: country |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1783821218.4609375 |
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num_examples: 12900 |
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- name: validation |
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num_bytes: 1746232603.9765625 |
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num_examples: 12700 |
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download_size: 3533048242 |
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dataset_size: 3530053822.4375 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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--- |
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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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