Glove-based sign language recognition solution to assist communication for deaf users

dc.contributor.authorJose Emiliano Lopez-Noriega
dc.contributor.authorMiguel Ivan Fernandez-Valladares
dc.contributor.authorVíctor Uc-Cetina
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T14:47:53Z
dc.date.available2026-03-22T14:47:53Z
dc.date.issued2014
dc.descriptionCitaciones: 13
dc.description.abstractThis 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.
dc.identifier.doi10.1109/iceee.2014.6978268
dc.identifier.urihttps://doi.org/10.1109/iceee.2014.6978268
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/48604
dc.language.isoen
dc.sourceUniversidad La Salle
dc.subjectSign language
dc.subjectGesture
dc.subjectComputer science
dc.subjectConversation
dc.subjectGesture recognition
dc.subjectRobustness (evolution)
dc.subjectSoftware
dc.subjectSpeech recognition
dc.subjectAssistive technology
dc.subjectManual communication
dc.titleGlove-based sign language recognition solution to assist communication for deaf users
dc.typearticle

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