Virtual Reality Tool for Learning Sign Language in Spanish

Language is the means of human access to the world. Languages have the virtue of opening up alternative ways of thinking and understanding the place people inhabit, relating to it, expanding it and modifying it. As a possibility of communication, languages open up opportunities to relate to other people, to get closer to them and to develop a broader understanding of the social and the human elements [1]. This research presents a visual tool designed to allow the learning of multiple words that are part of Spanish Sign Language (SSL) through an anthropomorphic model that is completely manipulable and programmable.

[1]  Carlos D. Martínez-Hinarejos,et al.  Sign Language Gesture Recognition Using HMM , 2017, IbPRIA.

[2]  Carlos Balaguer,et al.  Sign Language Representation by TEO Humanoid Robot: End-User Interest, Comprehension and Satisfaction , 2019, Electronics.

[3]  Yongyan Zheng,et al.  Motivation for Learning Spanish as a Foreign Language: The Case of Chinese L1 Speakers at University Level , 2019, Círculo de Lingüística Aplicada a la Comunicación.

[4]  H. Lane.  A Chronology of the Oppression of Sign Language in France and the United States , 2017 .

[5]  M. Carreiras,et al.  Language modality shapes the dynamics of word and sign recognition , 2019, Cognition.

[6]  Muhammad Modi bin Lakulu,et al.  A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017 , 2018, Sensors.

[7]  Hyun-Tae Jeong,et al.  Sensor Positioning and Data Acquisition for Activity Recognition using Deep Learning , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).

[8]  J. Goodrich,et al.  Inhibitory Control of Spanish-Speaking Language-Minority Preschool Children: Measurement and Association With Language, Literacy, and Math Skills , 2017, Journal of learning disabilities.

[9]  Mark Amengual,et al.  Phonological activation of first language (Spanish) and second language (English) when learning third language (Slovak) novel words , 2018, International Journal of Bilingualism.

[10]  Jiyoun Lim,et al.  Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning , 2019, Sensors.

[11]  Jennifer Beal Dr..  University American Sign Language (ASL) Second Language Learners: Receptive and Expressive ASL Performance , 2020 .

[12]  Amelec Viloria,et al.  Analysis of Patterns in the University World Rankings Webometrics, Shanghai, QS and SIR-SCimago: Case Latin America , 2018, DMBD.

[13]  Amelec Viloria,et al.  Methodology for the Design of a Student Pattern Recognition Tool to Facilitate the Teaching - Learning Process Through Knowledge Data Discovery (Big Data) , 2018, DMBD.

[14]  D. Moher,et al.  Sign Language and Spoken Language for Children With Hearing Loss: A Systematic Review , 2016, Pediatrics.

[15]  R. Wilbur,et al.  Age of acquisition effects differ across linguistic domains in sign language: EEG evidence , 2019, Brain and Language.

[16]  Xin Yu,et al.  Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison , 2020, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

[17]  Manuel Perea,et al.  Automatic use of phonological codes during word recognition in deaf signers of Spanish Sign Language , 2018 .

[18]  S. Goldin-Meadow,et al.  The influence of communication mode on written language processing and beyond , 2015, Behavioral and Brain Sciences.

[19]  Amelec Viloria,et al.  Methodology for Obtaining a Predictive Model Academic Performance of Students from First Partial Note and Percentage of Absence , 2016 .

[20]  Manuel Carreiras,et al.  LSE-Sign: A lexical database for Spanish Sign Language , 2015, Behavior Research Methods.

[21]  A Spanish Sign Language (LSE) Adaptation of the Communicative Development Inventories. , 2019, Journal of deaf studies and deaf education.

[22]  Richard Bowden,et al.  Sign Language Production using Neural Machine Translation and Generative Adversarial Networks , 2018, BMVC.