Guri10/Deepfake-Audio-Detection-with-XAI
This project focuses on detecting deepfake audio using advanced neural network architectures like VGG16, MobileNet, ResNet, and custom CNNs. It incorporates explainable AI (XAI) methods like LIME, Grad-CAM, and SHAP to enhance detection accuracy and provide insights into model predictions.
This tool helps you determine if an audio recording is a deepfake or authentic. You provide an audio file, and it tells you whether the sound has been artificially generated, along with explanations for its decision. This is ideal for professionals who need to verify the authenticity of spoken audio, such as journalists, researchers, or legal professionals.
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Use this if you need to reliably identify fabricated audio content and understand why the detection system made its judgment.
Not ideal if you are looking to detect other forms of media manipulation, such as deepfake video, or if you need to analyze music or non-speech audio.
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Feb 16, 2024
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