Quevedo: Annotation and Processing of Graphical Languages

Autor/a: SEVILLA, Antonio F. G.; DÍAZ ESTEBAN, Alberto; LAHOZ-BAGONECHEA, José María
Año: 2022
Editorial: European Language Resources Association
Tipo de código: Copyright
Soporte: Digital


Lingüística » Sistemas de transcripción de las Lenguas de Signos


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.

En Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 2022).