Quevedo: Annotation and Processing of Graphical Languages

Antonio F. G. Sevilla, Alberto Díaz Esteban, José María Lahoz-Bengoechea

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.
Anthology ID:
2022.lrec-1.269
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2528–2535
Language:
URL:
https://aclanthology.org/2022.lrec-1.269
DOI:
Bibkey:
Cite (ACL):
Antonio F. G. Sevilla, Alberto Díaz Esteban, and José María Lahoz-Bengoechea. 2022. Quevedo: Annotation and Processing of Graphical Languages. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2528–2535, Marseille, France. European Language Resources Association.
Cite (Informal):
Quevedo: Annotation and Processing of Graphical Languages (Sevilla et al., LREC 2022)
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