| Abstract |
In this article, we present Quevedo, a software tool we have developed for the
task of automatic processing of graphical languages. These are languages which
use images to convey meaning, relying not only on the shape of symbols but also
on their spatial arrangement in the page, and relative to each other. When
presented in image form, these languages require specialized computational
processing which is not the same as usually done either for natural language
processing or for artificial vision. Quevedo enables this specialized
processing, focusing on a data-based approach. As a command line application and
library, it provides features for the collection and management of image
datasets, and their machine learning recognition using neural networks and
recognizer pipelines. This processing requires careful annotation of the source
data, for which Quevedo offers an extensive and visual web-based annotation
interface. In this article, we also briefly present a case study centered on the
task of SignWriting recognition, the original motivation for writing the
software. Quevedo is written in Python, and distributed freely under the Open
Software License version 3.0.
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| Citation |
@InProceedings{sevilla_quevedo_2022,
author = {Sevilla, Antonio F. G. and Díaz Esteban, Alberto and Lahoz-Bengoechea, José María},
title = {Quevedo: Annotation and Processing of Graphical Languages},
booktitle = {Proceedings of the Language Resources and Evaluation Conference},
month = {June},
year = {2022},
address = {Marseille, France},
publisher = {European Language Resources Association},
pages = {2528--2535},
url = {https://aclanthology.org/2022.lrec-1.269}
}
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