BUILDING A FAST MULTILINGUAL OCR MODEL WITH SYNTHETIC DATA

Summary from the TLDR AI newsletter

NEMOTRON OCR V2, developed using synthetic data, is a fast, accurate multilingual OCR model achieving significant accuracy improvements, lowering NED scores to near-zero for non-English languages. Utilizing a synthetic data pipeline with mOSCAR text and diverse fonts, the model trains with pixel-perfect annotations across languages, enabling generalization to real-world documents. The unified architecture reuses feature maps, achieving speeds of 34.7 pages/second on a single A100 GPU, outperforming specialized models in diverse language OCR tasks.