DocumentCode :
179875
Title :
Glove-based sign language recognition solution to assist communication for deaf users
Author :
Lopez-Noriega, Jose Emiliano ; Fernandez-Valladares, Miguel Ivan ; Uc-Cetina, Victor
Author_Institution :
Dept. de Ingenierias, Univ. La Salle Noroeste, Ciudad Obregon, Mexico
fYear :
2014
fDate :
Sept. 29 2014-Oct. 3 2014
Firstpage :
1
Lastpage :
6
Abstract :
This manuscript presents the research and development of a software that help deaf-mute communication by identifying the position of the fingers of the hand with 5DT gloves. The sign language is adopted by nearly all people with hearing deficiency, making it their main form of communication, but this communication is only successfully achieved if all the participants of the conversation are familiar with the sign language. The goal is to be able to translate hand signs into words and phrases with the possibility to send audio signals to allow deaf-mute users to communicate to people not familiar with the sign language. The recognition of hand gestures is accomplished using a neural network tested using five different training algorithms. A cross-validation experiment is provided to illustrate the robustness of our methods.
Keywords :
audio signal processing; data gloves; handicapped aids; human computer interaction; language translation; neural nets; research and development; sign language recognition; software engineering; 5DT gloves; audio signals; deaf users; deaf-mute communication assistance; finger position identification; glove-based sign language recognition solution; hand gesture recognition; hand sign translation; hearing deficiency; neural network; software research-and-development; Assistive technology; Gesture recognition; Neural networks; Neurons; Real-time systems; Software; Training; algorithms; data gloves; neural networks; signs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering, Computing Science and Automatic Control (CCE), 2014 11th International Conference on
Conference_Location :
Campeche
Print_ISBN :
978-1-4799-6228-0
Type :
conf
DOI :
10.1109/ICEEE.2014.6978268
Filename :
6978268
Link To Document :
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