Deciphering Deception-LSTM Combats Deepfake Audios
It's safe to say that the proliferation of synthetically generated media, particularly Deepfakes, has raised significant concerns regarding privacy, security, and integrity of digital content. There is a lot of research to detect these deep-fakes, however we believe audio deepfake detection is an ever evolving technology which needs to conquer deepfake generation techniques. In this paper, we propose a Long Term Short Memory model to classify real and fake audios and discuss how different hyperparameters affect the results. Four models have been tested with four different optimisers each to conclude the best model and optimiser for deepfake audio detection.
Authors
- Mahesh Jangid (ORCID: https://orcid.org/0000-0001-5697-8786)
- Yushsvi Acharya
- Jahanvi Tyagi
Institutions
- Manipal Academy of Higher Education (IN)
- Manipal University Jaipur
Publication Details
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1109/ictacs62700.2024.10841007
- Primary Topic
- Digital Media Forensic Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00