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---
library_name: PyLaia
license: mit
tags:
- PyLaia
- PyTorch
- Handwritten text recognition
metrics:
- CER
- WER
language:
- 'no'
---
# Hugin-Munin handwritten text recognition
This model performs Handwritten Text Recognition in Norwegian. It was was developed during the [HUGIN-MUNIN project](https://hugin-munin-project.github.io/).
## Model description
The model has been trained using the PyLaia library on the [NorHand](https://zenodo.org/record/6542056) document images.
Line bounding boxes were improved using a post-processing step.
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 | 2.33 | 5.62 |
| val | 8.20 | 24.75 |
| test | 7.81 | 23.3 |
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](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-73/) published by the National Library of Norway.
| set | CER (%) | WER (%) |
| ----- | ---------- | --------- |
| train | 2.62 | 6.13 |
| val | 7.01 | 19.75 |
| test | 6.75 | 18.22 |
## How to use
Please refer to the PyLaia library page (https://pypi.org/project/pylaia/) to use this model.
# Cite us!
```bibtex
@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}
}
``` |