All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection. (arXiv:2307.15555v1 [cs.SD])

Recent advances in deep learning and computer vision have made the synthesis
and counterfeiting of multimedia content more accessible than ever, leading to
possible threats and dangers from malicious users. In the audio field, we are
witnessing the growth of speech deepfake generation techniques, which solicit
the development of synthetic speech detection algorithms to counter possible
mischievous uses such as frauds or identity thefts. In this paper, we consider
three different feature sets proposed in the literature for the synthetic …

audio computer computer vision deepfake deep learning detection feature fusion growth malicious speech synthetic techniques threats