Filipino Sign Language (FSL) is a multi-modal language that is composed of manual signlas and non-manual signals. Very minimal research is done regarding non-manual signals (Martinez and Cabalfin, 2008) despite the fact that non-manual signals play a significant role in conversations as it can be mixed freely with manual signals (Cabalfin et al., 2012). For other Sign Languages, there have been numerous researches regarding non-manual; however, most of these focused on the semantic and/or lexical functions only. Research on facial expressions in sign language that convey emotions or feelings and degrees of adjectives is very minimal. In this research, an analysis and recognition of non-manual signals in Filipino Sign Language are performed. The non-manual signals included are Types of Sentences (i.e. Statement, Question, Exclamation), Degrees of Adjectives (i.e. Absence, Presence, High Presence), and Emotions (i.e. Happy, Sad, Fast-approaching danger, stationary danger). The corpus was built with the help of the FSL Deaf Professors, and the 5 Deaf participants who signed 5 sentences for each of the types in front of Microsoft Kinect sensor. Genetic Algorithm is applied for the feature selection, while Artificial Neural Network and Support Vector Machine is applied for classification.
Keywords
Computer recognition of sign language and steps towards automatic annotation
@inproceedings{rivera:18040:sign-lang:lrec,
author = {Rivera, Joanna Pauline and Ong, Clement},
title = {Recognizing Non-manual Signals in {Filipino} {Sign} {Language}},
pages = {177--184},
editor = {Bono, Mayumi and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Osugi, Yutaka},
booktitle = {Proceedings of the {LREC2018} 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community},
maintitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Miyazaki, Japan},
day = {12},
month = may,
year = {2018},
isbn = {979-10-95546-01-6},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/18040.pdf}
}