A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

Aneela Pervez

doi:10.5281/zenodo.20824576

June 24, 2026Open Access

A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

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Key Points

The study aims to develop a comprehensive dashboard for analyzing synthetic media across various modalities.
Introduced a five-modality forensic dashboard for synthetic media analysis.
Combined multiple technologies: automated fact-checking, audio forensics, image forgery detection, video classification, and lip-sync detection.
Deployed the system on HuggingFace Spaces for accessibility.
Demonstrated effective detection capabilities across all modalities.
Improved accuracy in identifying synthetic media compared to existing methods.
Facilitated a faster and more integrated approach to media verification.

Implication

Study implements a multimodal forensic dashboard for synthetic media analysis, suggesting improved detection capabilities.

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

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Cite This Study

Aneela Pervez (2026) studied this question.

synapsesocial.com/papers/6a3e1a93030ad1a9b309301f https://doi.org/10.5281/zenodo.20824576

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A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

Key Points

Implication

Abstract

Discussion

Cite This Study

A Modular Heuristic Framework for Multimodal Synthetic Media Analysis

Key Points

Implication

Abstract

Discussion

Cite This Study

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