End-to-End Multimodal Data Augmentation and Adversarial Robustness Benchmark with AugLy for Images, Text, Audio, and PyTorch

MarkTechPost · 2 weeks ago · 48

The article presents an end-to-end multimodal augmentation and robustness workflow using AugLy for images, text, and audio, with deterministic synthetic datasets and metadata tracking wired into PyTorch pipelines. It generates the audio dataset at a sample rate of 16000 Hz. As a result, the workflow supports measuring robustness under image distortion and text adversarial perturbations (including Unicode obfuscation and adversarial training) while keeping experiments reproducible.