SpeechAntiSpoofingBenchmarks/ASVspoof5

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

notes example:

{"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

from datasets import load_dataset

ds = load_dataset("SpeechAntiSpoofingBenchmarks/ASVspoof5", split="test")
print(ds[0])

Stats

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`.

Citation

@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