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AT-ADD Track 2
This repository hosts Track 2 of the AT-ADD All-Type Audio Deepfake Detection Challenge. It contains the released audio splits and privacy-preserving sample-level metadata for non-commercial academic research and education.
Access
This is a gated dataset. Sign in to Hugging Face, review the access agreement, complete the short access form, and click Agree and access dataset. Access is granted automatically after acceptance.
Direct repository access is personal, and access credentials must not be shared. Redistribution is permitted only for non-commercial academic research or education under the conditions in the AT-ADD Dataset Access Agreement, including carrying the agreement with each copy and respecting the original licenses and terms of third-party source material.
Metadata
Privacy-preserving metadata is provided under meta_label/:
meta_label/t2_train_meta.csv— 146,781 recordsmeta_label/t2_dev_meta.csv— 91,069 recordsmeta_label/t2_eval_meta.csv— 229,373 records
Each CSV row corresponds to one audio clip and uses UTF-8 with BOM. Track 2 metadata fields are:
name, type, label, source, source_id, speaker_id, generation_task, generator, caption
- means unavailable or not applicable. See meta_label/README.md for field and privacy details.
Responsible use and citation
The dataset may be used only for non-commercial academic research and education. Users must respect third-party source licenses, privacy conditions, attribution requirements, and redistribution restrictions. If a rights holder or source provider raises a complaint or requests removal, the organizers may restrict or remove the affected content at any time; users who are notified must stop using and redistributing it. Publications or public results using this dataset should cite the official AT-ADD paper and acknowledge the dataset.
Questions, rights-holder concerns, or deletion requests may be submitted through this repository's Community tab.
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