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.

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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
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article

Deciphering Deception-LSTM Combats Deepfake Audios

Mahesh Jangid, Yushsvi Acharya, Jahanvi Tyagi
Digital Media Forensic Detection
article

Deciphering Deception-LSTM Combats Deepfake Audios

Mahesh Jangid, Yushsvi Acharya, Jahanvi Tyagi
article en

Abstract

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.

Manipal Academy of Higher Education (IN), Manipal University Jaipur
Openalex Percentile: Top 74%
Digital Media Forensic Detection
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