April 5, 2024, 4:48 a.m. | Jiangyan Yi, Chenglong Wang, Jianhua Tao, Chu Yuan Zhang, Cunhang Fan, Zhengkun Tian, Haoxin Ma, Ruibo Fu

cs.CL updates on arXiv.org arxiv.org

arXiv:2211.06073v2 Announce Type: replace-cross
Abstract: Many datasets have been designed to further the development of fake audio detection. However, fake utterances in previous datasets are mostly generated by altering timbre, prosody, linguistic content or channel noise of original audio. These datasets leave out a scenario, in which the acoustic scene of an original audio is manipulated with a forged one. It will pose a major threat to our society if some people misuse the manipulated audio with malicious purpose. Therefore, …

arxiv audio benchmarks cs.cl cs.sd dataset detection eess.as fake type

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