A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

This paper introduces a proof-of-concept five-modality forensic dashboard for synthetic media analysis, combining automated fact-checking (DeBERTa-v3), audio forensics (Wav2Vec2, AST, CLAP), image forgery detection (ResNet-18 + Transformer), video deepfake classification (ViT + OpenCLIP), and lip-sync anomaly detection (LSE-Net). Deployed on HuggingFace Spaces at https://huggingface.co/spaces/aneela-pervez/DEEP-FAKE-DETECTOR

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-24
DOI
https://doi.org/10.5281/zenodo.20824576
Primary Topic
Digital Media Forensic Detection
Type
preprint
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preprint

A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

Aneela Pervez
Zenodo (CERN European Organization for Nuclear Research)
Digital Media Forensic Detection
preprint

A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

Aneela Pervez
preprint en

Abstract

This paper introduces a proof-of-concept five-modality forensic dashboard for synthetic media analysis, combining automated fact-checking (DeBERTa-v3), audio forensics (Wav2Vec2, AST, CLAP), image forgery detection (ResNet-18 + Transformer), video deepfake classification (ViT + OpenCLIP), and lip-sync anomaly detection (LSE-Net). Deployed on HuggingFace Spaces at https://huggingface.co/spaces/aneela-pervez/DEEP-FAKE-DETECTOR

Zenodo (CERN European Organization for Nuclear Research)
GIFT University (PK)
Peace, Justice and strong institutions
Digital Media Forensic Detection
DOIOpen Access PDFOpenAlex
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