DeepFake-o-meter
An open-source platform for robust deepfake detection platform, supporting various media types including audio and video. Continuously updated with the latest detection algorithms.
Visit Project WebsiteRoles: Project Manager
An open-source platform for robust deepfake detection platform, supporting various media types including audio and video. Continuously updated with the latest detection algorithms.
Visit Project WebsiteRoles: Project Manager
Investigating the use of segmental speech features for more robust and nuanced deepfake audio detection, building on collaboration with other researchers.
View Related PreprintRoles: Co-Researcher
We aim to survey the landscape of DeepFake generation methods and their state-of-the-art performance.
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DART is a cross-disciplinary, multi-institutional, user-centered effort to develop games to help older adults recognize and navigate scams.
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Our objective is to develop a multi-modal deepfake detection model that integrates audio and video analysis to overcome the limitations of existing methods.
Roles: Co-Researcher
Development and curation of a large-scale, diverse dataset specifically designed to train and benchmark deepfake audio detection models.
Roles: Lead Researcher
Research project focusing on identifying unique artifacts left by neural vocoders in AI-synthesized voices to improve deepfake audio detection accuracy.
View Related PublicationRoles: Lead Researcher
Our objective is to develop methodologies for synthetic audio detection through the identification of the neural vocoder employed during the generation process.
Visit Project WebsiteRoles: Lead Researcher
Explore more of my coding and research projects on my GitHub profile.
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