WaveFake: A Data Set to Facilitate Audio DeepFake Detection
This is the code repository for our NeurIPS 2021 (Track on Datasets and Benchmarks) paper WaveFake.
Deep generative modeling has the potential to cause significant harm to society.
Recognizing this threat, a magnitude of research into detecting so-called “Deepfakes” has emerged.
This research most often focuses on the image domain, while studies exploring generated audio signals have – so far – been neglected.
In this paper, we aim to narrow this gap.
We present a novel data set, for which we collected ten sample sets from six different network architectures, spanning two languages.
We analyze the frequency statistics comprehensively, discovering subtle differences between the architectures, specifically among the higher frequencies.
Additionally, to facilitate further development of