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Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective [PDF]
International ACM SIGACCESS Conference on Computers and Accessibility, 2019 Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and ...
Danielle Bragg +11 more
semanticscholar +1 more source
, 2020 This volume has arisen from a three-part, five-year study on language contact among multilingual sign language users, which has three strands: cross-signing, sign-switching, and sign-speaking. These phenomena are only sparsely documented so far, and thus
core +1 more source
The ATIS sign language corpus [PDF]
, 2008 Systems that automatically process sign language rely on appropriate data. We therefore present the ATIS sign language corpus that is based on the domain of air travel information. It is available for five languages, English, German, Irish sign language,
Morrissey, Sara +6 more
core +2 more sources
Hand gestures for emergency situations: A video dataset based on words from Indian sign language
Data in Brief, 2020 Automatic sign language recognition provides better services to the deaf as it avoids the existing communication gap between them and the rest of the society.
V. Adithya, R. Rajesh
doaj +1 more source
Dicta-Sign - Use of a Multilingual Corpus to Improve Sign Language Technology
, 2010 International audienceDicta-Sign is a three-year EU-funded research project which started in January 2009. It aims to improve online communication for Deaf people by promoting the development of sign language based web applications.
Worseck, Satu +12 more
core +3 more sources
Artificial Intelligence Technologies for Sign Language
Sensors, 2021 AI technologies can play an important role in breaking down the communication barriers of deaf or hearing-impaired people with other communities, contributing significantly to their social inclusion.
Ilias Papastratis +4 more
doaj +1 more source
Sign Language Recognition: High Performance Deep Learning Approach Applyied To Multiple Sign Languages [PDF]
E3S Web of Conferences, 2022 In this paper we present a high performance Deep Learning architecture based on Convolutional Neural Network (CNN). The proposed architecture is effective as it is capable of recognizing and analyzing with high accuracy different Sign language datasets ...
El Zaar Abdellah +2 more
doaj +1 more source
Hand in hand: automatic sign Language to English translation [PDF]
, 2007 In this paper, we describe the first data-driven automatic sign-language-to- speech translation system. While both sign language (SL) recognition and translation techniques exist, both use an intermediate notation system not directly intelligible for ...
Morrissey, Sara +4 more
core +2 more sources
Self-Emphasizing Network for Continuous Sign Language Recognition [PDF]
AAAI Conference on Artificial Intelligence, 2022 Hand and face play an important role in expressing sign language. Their features are usually especially leveraged to improve system performance. However, to effectively extract visual representations and capture trajectories for hands and face, previous ...
Lianyu Hu +3 more
semanticscholar +1 more source
Peruvian Sign Language Recognition Using Recurrent Neural Networks
, 2022 Deaf people generally face difficulties in their daily lives when they try to communicate with hearing people, this is due to the lack of sign language knowledge in the country.
Barrientos-Villalta, Geraldine Fiorella +2 more
core +1 more source