Virtual sign : a real time bidirectional translator of portuguese sign language

• Main Author: Escudeiro, Paula
• Publication Date: 2015
• Other Authors: Escudeiro, Nuno, Reis, Rosa, Lopes, Jorge, Norberto, Marcelo, Baltazar, Ana Bela, Barbosa, Maciel, Bidarra, José
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10400.2/4695
• topic: Portuguese Sign Language (LGP); Education; Deaf; Kinect; Machine learning; Open CV; Sensor gloves; Translator; Support vector machines; Dynamic time warping; Avatar

Promoting equity, equal opportunities to all and social inclusion of people with disabilities is a concern of modern societies at large and a key topic in the agenda of European Higher Education. Despite all the progress, we cannot ignore the fact that the conditions provided by the society for the deaf are still far from being perfect. The communication with deaf by means of written text is not as efficient as it might seem at first. In fact, there is a very deep gap between sign language and spoken/written language. The vocabulary, the sentence construction and the grammatical rules are quite different among these two worlds. These facts bring significant difficulties in reading and understanding the meaning of text for deaf people and, on the other hand, make it quite difficult for people with no hearing disabilities to understand sign language. The deployment of tools to assist the daily communication, in schools, in public services, in museums and other, between deaf people and the rest may be a significant contribution to the social inclusion of the deaf community. The work described in this paper addresses the development of a bidirectional translator between Portuguese Sign Language and Portuguese text. The translator from sign language to text resorts to two devices, namely the Microsoft Kinect and 5DT Sensor Gloves in order to gather data about the motion and shape of the hands. The hands configurations are classified using Support Vector Machines. The classification of the movement and orientation of the hands are achieved through the use of Dynamic Time Warping algorithm. The translator exhibits a precision higher than 90%. In the other direction, the translation of Portuguese text to Portuguese Sign Language is supported by a 3D avatar which interprets the entered text and performs the corresponding animations.