Fighting AI with AI: Fake Speech Detection Using Deep Learning

Malik H, Changalvala R. Fighting AI with AI: Fake Speech Detection Using Deep Learning. In: AES Conference: 2019 AES International Conference on Audio Forensics. Audio Engineering Society; 2019. Paper 29. Available from: https://aes.org/publications/elibrary-page/?id=20479

@inproceedings{Malik2019_20479,
  author = {Malik, Hafiz and Changalvala, Raghavendar},
  title = {{Fighting AI with AI: Fake Speech Detection Using Deep Learning}},
  booktitle = {AES Conference: 2019 AES International Conference on Audio Forensics},
  note = {Paper 29},
  year = {2019},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=20479}
}

TY  - CPAPER
TI  - Fighting AI with AI: Fake Speech Detection Using Deep Learning
AU  - Malik, Hafiz
AU  - Changalvala, Raghavendar
T2  - AES Conference: 2019 AES International Conference on Audio Forensics
M1  - Paper 29
PY  - 2019
DA  - 2019/06/06
UR  - https://aes.org/publications/elibrary-page/?id=20479
PB  - Audio Engineering Society
LA  - en
AB  - Voice cloning technologies have found applications in a variety of areas ranging from personalized speech interfaces to advertisement, video gaming, and so on. Existing voice cloning systems are capable of learning speaker characteristics from few samples and generating perceptually indistinguishable speech. These advances pose new security and privacy threats to voice-driven interfaces. This paper presents a deep learning-based framework for learning cloned speech synthesis models and the bona-?de speech production processes. To this end, a convolutional neural network is trained and tested on spectrogram estimated from input audio recordings. Performance of the proposed method is evaluated on cloned and bona-?de audios. Experimental results indicate that the proposed method is capable of detecting bona-?de and cloned audios with a close to perfect accuracy.
ER  -