Turkish sign language alphabet translator

Yalcin, Metehan; Ilgaz, Sema; Ozkul, Gunduz; Yildiz, Solen Kumbay

doi:10.1109/siu.2018.8404478

Cited by 6 publications

(1 citation statement)

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“…In the last method, the techniques in the first and second methods are used together with the sensors [4]. For Turkish sign language, Yalçın et al tried to identify all the letters in the Turkish alphabet with the help of a single glove and obtain them visually [5]. Another study is on the translation of the sign language with a data glove, which is a portable system with sensors on it [6].…”

Section: Introductionmentioning

confidence: 99%

İşitme ve Konuşma Güçlüğü Çekenlere Yardımcı Olan Eldiven Tasarımı

Orhanbulucu

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Kurt

et al. 2020

European Journal of Science and Technology

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Communication is the proper transfer of feelings and thoughts to others. The most used communication among people is verbal communication, which is based on hearing and speech. However, it is observed that individuals with disabilities due to hearing or speech loss either do not use this communication method or can use it limitedly. These individuals communicate with each other through methods such as sign language, alphabet created using hand or finger movements. In this study, a system that can perceive sign language has been developed for individuals with speech and hearing impairments in order to communicate more easily with each other and with individuals who do not know sign language. Flex sensors are placed on the glove to be used in the developed system. Flex sensors were connected to Arduino with voltage divider circuits and varying voltage values were taken. In this system, a new sign language was developed based on the existing sign language. In the developed system, each combination of finger and hand gestures represents a separate word. These combinations are logically numerical sets consisting of logic 0 and logic 1 in computer language. Finger movements corresponding to the words to be used in the study were introduced to the developed system. The words corresponding to the combinations have been transferred to the system library and stored. In the study, the most used words in daily life were determined and test studies were conducted. A word introduced to the system in return for each combination made by the hand and finger movements performed by the user was exported via the screen.

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Section: Introductionmentioning

confidence: 99%