Datasets:
File size: 2,616 Bytes
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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
Contact: k.n.borodin@mtuci.ru
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