WueNLP/Synthdog-Multilingual-100

Synthdog Multilingual

The Synthdog dataset created for training in Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model.

Using the official Synthdog code, we created >1 million training samples for improving OCR capabilities in Large Vision-Language Models.

Dataset Details

We provide the images for download in two .tar.gz files. Download and extract them in folders of the same name (so cat images.tar.gz.* | tar xvzf -C images; tar xvzf images.tar.gz -C images_non_latin). The image path in the dataset expects images to be in those respective folders for unique identification.

Every language has the following amount of samples: 500,000 for English, 10,000 for non-Latin scripts, and 5,000 otherwise.

Text is taken from Wikipedia of the respective languages. Font is GoNotoKurrent-Regular.

Note: Right-to-left written scripts (Arabic, Hebrew, ...) are unfortunatly writte correctly right-to-left but also bottom-to-top. We were not able to fix this issue. However, empirical results in Centurio suggest that this data is still helpful for improving model performance.

Citation

BibTeX:

@article{centurio2025,
  author       = {Gregor Geigle and
                  Florian Schneider and
                  Carolin Holtermann and
                  Chris Biemann and
                  Radu Timofte and
                  Anne Lauscher and
                  Goran Glava\v{s}},
  title        = {Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model},
  journal      = {arXiv},
  volume       = {abs/2501.05122},
  year         = {2025},
  url          = {https://arxiv.org/abs/2501.05122},
  eprinttype    = {arXiv},
  eprint       = {2501.05122},
}