Update README.md

README.md

@@ -27,33 +27,37 @@ This model performs Handwritten Text Recognition in Latin on medieval documents.
 ## Model description
 
 The model was trained using the PyLaia library on two medieval datasets:
-* [Himanis](https://demo.arkindex.org/browse/5000e248-a624-4df1-8679-1b34679817ef?top_level=true&folder=true) (French)
-* [HOME-Alcar](https://demo.arkindex.org/browse/46b9b1f4-baeb-4342-a501-e2f15472a276?top_level=true&folder=true) (Latin)
+* [Himanis](https://demo.arkindex.org/browse/5000e248-a624-4df1-8679-1b34679817ef?top_level=true&folder=true) (French);
+* [HOME-Alcar](https://demo.arkindex.org/browse/46b9b1f4-baeb-4342-a501-e2f15472a276?top_level=true&folder=true) (Latin).
 
-For training, text-lines were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
+Training images were resized with a fixed height of 128 pixels, keeping the original aspect ratio.
 
-An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the HOME Alcar training set.
+An external 6-gram character language model can be used to improve recognition. The language model is trained on the text from the HOME-Alcar training set.
 
 ## Evaluation results
 
 On HOME-Alcar text lines, the model achieves the following results:
 
-| set   | Language model | CER (%)    | WER (%) | N lines   |
+| set   | Language model | CER (%)    | WER (%) | lines   |
 |:------|:---------------| ----------:| -------:|----------:|
 | test  | no             | 8.35       | 26.15   |     6,932 |
 | test  | yes            | 7.85       | 23.20   |     6,932 |
 
 ## How to use?
 
-Please refer to the [documentation](https://atr.pages.teklia.com/pylaia/).
+Please refer to the [PyLaia documentation](https://atr.pages.teklia.com/pylaia/usage/prediction/) to use this model.
 
 ## Cite us!
 
 ```bibtex
-@inproceedings{pylaia-lib,
-    author = "Tarride, Solène and Schneider, Yoann and Generali, Marie and Boillet, Melodie and Abadie, Bastien and Kermorvant, Christopher",
-    title = "Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library",
-    booktitle = "Submitted at ICDAR2024",
-    year = "2024"
+@inproceedings{pylaia2024,
+    author = {Tarride, Solène and Schneider, Yoann and Generali-Lince, Marie and Boillet, Mélodie and Abadie, Bastien and Kermorvant, Christopher},
+    title = {{Improving Automatic Text Recognition with Language Models in the PyLaia Open-Source Library}},
+    booktitle = {Document Analysis and Recognition - ICDAR 2024},
+    year = {2024},
+    publisher = {Springer Nature Switzerland},
+    address = {Cham},
+    pages = {387--404},
+    isbn = {978-3-031-70549-6}
 }
 ```