Hugin-Munin handwritten text recognition
This model performs Handwritten Text Recognition in Norwegian. It was developed during the HUGIN-MUNIN project.
Model description
The model has been trained using the PyLaia library on the NorHand document images. Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
Evaluation results
The model achieves the following results:
| set | CER (%) | WER (%) |
|---|---|---|
| train | 2.17 | 7.65 |
| val | 8.78 | 24.93 |
| test | 7.94 | 24.04 |
Results improve on validation and test sets when PyLaia is combined with a 6-gram language model. The language model is trained on this text corpus published by the National Library of Norway.
| set | CER (%) | WER (%) |
|---|---|---|
| train | 2.40 | 8.10 |
| val | 7.45 | 19.75 |
| test | 6.55 | 18.2 |
How to use
Please refer to the PyLaia library page and wiki to use this model.
Cite us!
@inproceedings{10.1007/978-3-031-06555-2_27,
author = {Maarand, Martin and Beyer, Yngvil and K\r{a}sen, Andre and Fosseide, Knut T. and Kermorvant, Christopher},
title = {A Comprehensive Comparison of Open-Source Libraries for Handwritten Text Recognition in Norwegian},
year = {2022},
isbn = {978-3-031-06554-5},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
url = {https://doi.org/10.1007/978-3-031-06555-2_27},
doi = {10.1007/978-3-031-06555-2_27},
booktitle = {Document Analysis Systems: 15th IAPR International Workshop, DAS 2022, La Rochelle, France, May 22–25, 2022, Proceedings},
pages = {399–413},
numpages = {15},
keywords = {Norwegian language, Open-source, Handwriting recognition},
location = {La Rochelle, France}
}
