Estudio de bases de datos para el reconocimiento automático de lenguas de signos

TitleEstudio de bases de datos para el reconocimiento automático de lenguas de signos
Publication TypeJournal Article
Year of Publication2020
AuthorsSantiago, DTilves, García-Mateo, C, Torres Guijarro, S, Docío Fernández, L, Castro, JLuis Alba
JournalHesperia. Anuario de filología hispánica
Volume22
Issue2
Pagination145-160
Date Published03/2020
ISSN1139-3181
KeywordsAnnotation, ANVIL, ASLR, Automatic Recognition, Deaf, ELAN, RALS, Sign Language Dataset
AbstractAutomatic sign language recognition (ASLR) is quite a complex task, not only for the difficulty of dealing with very dynamic video information, but also because almost every sign language (SL) can be considered as an under-resourced language when it comes to language technology. Spanish sign language (LSE) is one of those under-resourced languages. Developing technology for SSL implies a number of technical challenges that must be tackled down in a structured and sequential manner. In this paper, some problems of machine-learning- based ASLR are addressed. A review of publicly available datasets is given and a new one is presented. It is also discussed the current annotations methods and annotation programs. In our review of existing datasets, our main conclusion is that there is a need for more with high-quality data and annotations.
URLhttp://revistas.webs.uvigo.es/index.php/AFH/article/view/1658/1588
DOI10.35869/hafh.v22i0.1658
Citation Key671