metadata
language:
- en
- de
- fr
- it
- nl
- multilingual
tags:
- punctuation prediction
- punctuation
datasets: wmt/europarl
license: mit
widget:
- text: Ho sentito che ti sei laureata il che mi fa molto piacere
example_title: Italian
- text: Tous les matins vers quatre heures mon père ouvrait la porte de ma chambre
example_title: French
- text: Ist das eine Frage Frau Müller
example_title: German
- text: My name is Clara and I live in Berkeley California
example_title: English
metrics:
- f1
Work in progress
Classification report over all languages
precision recall f1-score support
0 0.99 0.99 0.99 47903344
. 0.94 0.95 0.95 2798780
, 0.85 0.84 0.85 3451618
? 0.88 0.85 0.87 88876
- 0.61 0.32 0.42 157863
: 0.72 0.52 0.60 103789
accuracy 0.98 54504270
macro avg 0.83 0.75 0.78 54504270
weighted avg 0.98 0.98 0.98 54504270
How to cite us
@article{guhr-EtAl:2021:fullstop,
title={FullStop: Multilingual Deep Models for Punctuation Prediction},
author = {Guhr, Oliver and Schumann, Anne-Kathrin and Bahrmann, Frank and Böhme, Hans Joachim},
booktitle = {Proceedings of the Swiss Text Analytics Conference 2021},
month = {June},
year = {2021},
address = {Winterthur, Switzerland},
publisher = {CEUR Workshop Proceedings},
url = {http://ceur-ws.org/Vol-2957/sepp_paper4.pdf}
}
@misc{https://doi.org/10.48550/arxiv.2301.03319,
doi = {10.48550/ARXIV.2301.03319},
url = {https://arxiv.org/abs/2301.03319},
author = {Vandeghinste, Vincent and Guhr, Oliver},
keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2.7},
title = {FullStop:Punctuation and Segmentation Prediction for Dutch with Transformers},
publisher = {arXiv},
year = {2023},
copyright = {Creative Commons Attribution Share Alike 4.0 International}
}