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| license: odc-by | |
| language: | |
| - en | |
| pretty_name: ASVspoof 5 (track 1, eval) | |
| task_categories: | |
| - audio-classification | |
| size_categories: | |
| - 100K<n<1M | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: test | |
| path: "data/test-*.parquet" | |
| tags: | |
| - anti-spoofing | |
| - audio-deepfake-detection | |
| - speech | |
| - benchmark | |
| - arena-ready | |
| arxiv: | |
| - "2408.08739" | |
| # ASVspoof 5 (track 1, eval) | |
| Benchmark-ready packaging of the **Track 1 (spoofing / deepfake detection) evaluation partition** of the ASVspoof 5 challenge, for speech anti-spoofing and synthetic / deepfake voice detection. | |
| ## Overview | |
| Track 1 is binary classification: **bonafide** (genuine human speech) vs. **spoof** (synthetic / converted speech). This packaging contains the full track_1 evaluation set. The original challenge is at https://www.asvspoof.org/. | |
| ## License & redistribution | |
| Redistributed under the **Open Data Commons Attribution License (ODC-By) v1.0**. See `LICENSE.txt`. Labels and the evaluation protocol are unmodified; audio is the original 16 kHz mono FLAC, embedded bit-exactly (no re-encode — a full decode probe of all 680,774 clips passed cleanly). | |
| ## Schema | |
| | Column | Type | Description | | |
| |--------|------|-------------| | |
| | `path` | `string` | `<utterance_id>.flac`, unique | | |
| | `audio` | `Audio(16000)` | 16 kHz mono FLAC | | |
| | `label` | `ClassLabel` | `"bonafide"` (0) / `"spoof"` (1) | | |
| | `notes` | `string` | JSON: `utterance_id`, `speaker_id`, `gender`, `codec`, `codec_id`, `source_id`, `attack_condition`, `attack_id` | | |
| `notes` example: | |
| ```json | |
| {"utterance_id": "E_0009538969", "speaker_id": "E_1607", "gender": "M", "codec": "C05", "codec_id": "2", "source_id": "E_0009486171", "attack_condition": "AC1", "attack_id": "A26"} | |
| ``` | |
| ## Quick Start | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("SpeechAntiSpoofingBenchmarks/ASVspoof5", split="test") | |
| print(ds[0]) | |
| ``` | |
| ## Stats | |
| | Stat | Value | | |
| |------|-------| | |
| | Total trials | 680,774 | | |
| | Bonafide | 138,688 | | |
| | Spoof | 542,086 | | |
| ## Source provenance | |
| - Original challenge: https://www.asvspoof.org/ | |
| - Evaluation protocol: `ASVspoof5.eval.track_1.tsv` | |
| ## Evaluation | |
| For evaluation instructions and submission format, see [`submissions/README.md`](submissions/README.md). | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{wang2024asvspoof5, | |
| title = {{ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale}}, | |
| author = {Wang, Xin and Delgado, H{\'e}ctor and Tak, Hemlata and others}, | |
| year = {2024}, | |
| booktitle = {ASVspoof Workshop 2024}, | |
| } | |
| ``` | |
| ## Maintainer | |
| Maintained by Kirill Borodin (SpeechAntiSpoofingBenchmarks). | |
| - Email: ~~k.n.borodin@mtuci.ru~~ (deprecated — use kborodin.research@gmail.com) | |
| - Telegram: [@korallll_ai](https://t.me/korallll_ai) | |