BabelFake: A Multilingual Audio-Visual DeepFake Benchmark
Reliable and practical audio-visual DeepFake detection requires benchmarks that reflect diverse linguistic contexts and modern data synthesis pipelines for visual as well as audio manipulations. However, existing datasets predominantly contain footage of English-speakers, often include outdated manipulation types, or overlook the audio modality. Further, many datasets feature individuals who did not consent to be used in DeepFake creation. We introduce BabelFake, a multilingual audio-visual DeepFake benchmark recorded with consenting participants. BabelFake contains 399k clips (1,323 hours) from 496 individuals spanning five languages (English, German, Italian, French, Spanish). Our modul...
| Authors | Carlotta Segna, Joel Tschesche, Anna Rohrbach |
|---|---|
| Primary category | cs.CV |
| Published | 5 October 2026 |
| Last updated at source | 8 October 2026 |
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