Dataset · Hugging Face

SpeechAntiSpoofingBenchmarks/DFADD

Name: DFADD
Creator: SpeechAntiSpoofingBenchmarks
License: mit
Keywords: task_categories:audio-classification, language:en, license:mit, size_categories:1K<n<10K, format:parquet, modality:audio, modality:text, library:datasets, library:dask, library:polars, library:mlcroissant, arxiv:2409.08731, region:us, anti-spoofing, audio-deepfake-detection

DFADD — Diffusion and Flow-Matching Based Audio Deepfake Dataset Benchmark-ready packaging of the DFADD test (eval) split (DFADD: The Diffusion and Flow-Matching Based Audio Deepfake Dataset, arXiv 2409.08731), a VCTK-derived dataset targeting the newest generation of high-quality TTS spoofing built on diffusion and flow-matching synthesizers. Overview Binary classification: bonafide (genuine VCTK recordings) vs. spoof (text-to-speech generated from VCTK… See the full description on the dataset page: https://huggingface.co/datasets/SpeechAntiSpoofingBenchmarks/DFADD.

View on Hugging FaceReport an issue

Author / organization	SpeechAntiSpoofingBenchmarks
License (as declared)	mit
Downloads	1.2K (as reported by Hugging Face)
Likes	0
Created	10 June 2026
Last updated at source	27 June 2026

anti-spoofingaudio-deepfake-detectionspeechbenchmarkarena-readydiffusionflow-matching

Embed this entry

<iframe src="https://silytics.si/embed/item/a98c135b-0e87-44dd-9fac-ca5ca80fc114" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

More from SpeechAntiSpoofingBenchmarks

SpeechAntiSpoofingBenchmarks/ASVspoof2021_DFDataset
SpeechAntiSpoofingBenchmarks/ASVspoof5Dataset
SpeechAntiSpoofingBenchmarks/ASVspoof2021_LADataset
SpeechAntiSpoofingBenchmarks/ASVspoof2019_LADataset
SpeechAntiSpoofingBenchmarks/ODSSDataset
SpeechAntiSpoofingBenchmarks/CVoiceFake_smallDataset

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.