SpeechAntiSpoofingBenchmarks/J-SPAW_LA
J-SPAW (LA track, eval) ⚠️ NON-COMMERCIAL USE ONLY The upstream J-SPAW dataset is released "For non-commercial use only" (see the J-SPAW repository). This packaging inherits that restriction: do not use it for any commercial purpose. It is provided solely for non-commercial academic research and benchmarking. The upstream terms are sparse and do not spell out redistribution; contact the original authors for any use beyond non-commercial research. Benchmark-ready… See the full description on the dataset page: https://huggingface.co/datasets/SpeechAntiSpoofingBenchmarks/J-SPAW_LA.
J-SPAW (LA track, eval)
## ⚠️ NON-COMMERCIAL USE ONLY The upstream J-SPAW dataset is released "For non-commercial use only" (see the J-SPAW repository). This packaging inherits that restriction: do not use it for any commercial purpose. It is provided solely for non-commercial academic research and benchmarking. The upstream terms are sparse and do not spell out redistribution; contact the original authors for any use beyond non-commercial research.
Benchmark-ready packaging of the LA (logical access) track of J-SPAW — the Japanese Speaker-verification and sPoofing-attacks recorded in-the-Wild dataset (Shiota et al., Interspeech 2025), for speech anti-spoofing / deepfake voice detection.
Overview
J-SPAW is a Japanese, in-the-wild corpus built to evaluate speaker verification and spoofing detection jointly, with a focus on physical-access (replay) scenarios. This repository packages only the dataset's LA track, which is the subset shipped as audio in the ver1 release:
- bonafide — genuine human speech (iPhone 8 microphone
M2), recorded across four acoustic environments (E1 quiet, E2 air-conditioner, E3 music, E4 outside). - spoof — LA-track attacks
L1/L2.
Binary classification: bonafide (genuine) vs. spoof. The full J-SPAW PA (physical-access / replay) track is not part of this ver1 audio release and is therefore not packaged here.
3 source clips shorter than 1.0 s were dropped (the Arena requires ≥ 1.0 s).
License & redistribution
Non-commercial use only — see the banner above and LICENSE.txt. Labels and the evaluation protocol are unmodified; audio is the original 16 kHz mono PCM WAV, embedded bit-exactly (no re-encode — a full decode probe of all 2,400 source clips passed cleanly).
Schema
notes example:
{"utterance_id": "F001_R1_E2_L1_BT", "speaker_id": "F001", "track": "LA", "attack": "L1", "record_env": "E2", "mic": null, "subset": "eval"}Quick Start
from datasets import load_dataset
ds = load_dataset("SpeechAntiSpoofingBenchmarks/J-SPAW_LA", split="test")
print(ds[0])Stats
Source provenance
- Paper: S. Shiota, S. Horie, K. Kanno, S. Takamichi, "J-SPAW: Japanese speaker verification and spoofing attacks recorded in-the-wild dataset", Interspeech 2025. DOI 10.21437/Interspeech.2025-352.
- Dataset: https://github.com/takamichi-lab/j-spaw
- Protocol:
metadata_LA.txt(ASVspoof-2021-style LA-track protocol).
Evaluation
For evaluation instructions and submission format, see `submissions/README.md`.
Citation
@inproceedings{shiota2025jspaw,
title = {{J-SPAW: Japanese speaker verification and spoofing attacks recorded in-the-wild dataset}},
author = {Shiota, Sayaka and Horie, Suzuka and Kanno, Kouta and Takamichi, Shinnosuke},
year = {2025},
booktitle = {Proc. Interspeech 2025},
pages = {3913--3917},
doi = {10.21437/Interspeech.2025-352},
}Maintainer
Maintained by Kirill Borodin (SpeechAntiSpoofingBenchmarks).
- Email: ~~k.n.borodin@mtuci.ru~~ (deprecated — use kborodin.research@gmail.com)
- Telegram: @korallll_ai
