SpeechAntiSpoofingBenchmarks/ASVspoof2019_LA

ASVspoof 2019 LA

Benchmark-ready packaging of the Logical Access (LA) evaluation partition from ASVspoof 2019 for speech anti-spoofing and synthetic voice detection.

Overview

This dataset contains the LA evaluation subset of the ASVspoof 2019 challenge. The task is binary classification: bonafide (genuine human speech) vs. spoof (synthetic or converted speech). The original dataset is available at https://www.asvspoof.org/index2019.html.

License & redistribution

This dataset is redistributed under the Open Data Commons Attribution License (ODC-By). See LICENSE.txt for the full text. The original dataset was not modified.

Schema

Column	Type	Description
path	string	Stable archive-relative path (e.g. LA_E_2834763.flac), unique within dataset
audio	Audio(16000)	Audio waveform, 16 kHz mono
label	ClassLabel	"bonafide" (index 0) or "spoof" (index 1)
notes	string	JSON with utterance_id, speaker_id, subset

notes example:

{"utterance_id": "LA_E_2834763", "speaker_id": "LA_0039", "subset": "eval"}

Quick Start

from datasets import load_dataset

ds = load_dataset("SpeechAntiSpoofingBenchmarks/ASVspoof2019_LA", split="test")
print(ds[0])
# {'path': 'LA_E_2834763.flac', 'audio': {'array': ..., 'sampling_rate': 16000},
#  'label': 1, 'notes': '{"utterance_id": "LA_E_2834763", ...}'}

Stats

Stat	Value
Total trials	71,237
Bonafide	7,355
Spoof	63,882

Source provenance

• Original dataset: https://www.asvspoof.org/index2019.html
• Evaluation protocol: protocols/ASVspoof2019.LA.cm.eval.trl.txt

Evaluation

For evaluation instructions and submission format, see submissions/README.md.

Citation

Original paper: https://arxiv.org/abs/1911.01601

arXiv version:

@misc{wang2020asvspoof2019largescalepublic,
      title={ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech},
      author={Xin Wang and Junichi Yamagishi and Massimiliano Todisco and Hector Delgado and Andreas Nautsch and Nicholas Evans and Md Sahidullah and Ville Vestman and Tomi Kinnunen and Kong Aik Lee and Lauri Juvela and Paavo Alku and Yu-Huai Peng and Hsin-Te Hwang and Yu Tsao and Hsin-Min Wang and Sebastien Le Maguer and Markus Becker and Fergus Henderson and Rob Clark and Yu Zhang and Quan Wang and Ye Jia and Kai Onuma and Koji Mushika and Takashi Kaneda and Yuan Jiang and Li-Juan Liu and Yi-Chiao Wu and Wen-Chin Huang and Tomoki Toda and Kou Tanaka and Hirokazu Kameoka and Ingmar Steiner and Driss Matrouf and Jean-Francois Bonastre and Avashna Govender and Srikanth Ronanki and Jing-Xuan Zhang and Zhen-Hua Ling},
      year={2020},
      eprint={1911.01601},
      archivePrefix={arXiv},
      primaryClass={eess.AS},
      url={https://arxiv.org/abs/1911.01601},
}

Peer-reviewed publication (Computer Speech & Language, 2020):

@article{wang2020asvspoof,
  title={ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech},
  author={Wang, Xin and Yamagishi, Junichi and Todisco, Massimiliano and Delgado, Hector and Nautsch, Andreas and Evans, Nicholas and Sahidullah, Md and Vestman, Ville and Kinnunen, Tomi and Lee, Kong Aik and others},
  journal={Computer Speech \& Language},
  volume={64},
  pages={101114},
  year={2020},
  publisher={Elsevier}
}

Maintainer

Contact: k.n.borodin@mtici.ru