Segmentation, Sign-Language, Algorithm


Segmentation is an important aspect of translating finger spelling of sign language into Latin alphabets. Although the sign language devices that are currently available can translate the finger spelling into alphabets, there is a limitation where the output is stored in a long continuous string without spaces between words. The system proposed in this work is meant to be used together with a text-generating glove device. The system used text input string and the string is then fed into the system, one character at a time, and then it is segmented into words that is semantically correct. The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. Based on the results, the system is able to properly segment words with acceptable accuracy.


Segmentasi adalah aspek penting dalam menterjemahkan ejaan bahasa isyarat ke dalam huruf Latin. Walaupun terdapat peranti bahasa isyarat yang menterjemahkan ejaan jari menjadi huruf, namun begitu, huruf-huruf yang dihasilkan disimpan dalam rentetan berterusan yang panjang tanpa jarak antara setiap perkataan. Sistem yang dicadangkan di dalam jurnal ini akan diselaraskan bersama dengan sarung tangan bahasa isyarat yang boleh menghasilkan teks. Sistem ini akan mengambil rentetan input teks di mana huruf akan dimasukkan satu persatu dan huruf-huruf itu akan disegmentasikan menjadi perkataan yang betul secara semantik. Kaedah pembahagian yang dicadangkan ialah segmentasi yang menggunakan pengaturcaraan dinamik dan kaedah kebarangkalian untuk mengsegmentasikan huruf-huruf tersebut berdasarkan padanan perkataan dengan pengkalan data di dalam Bahasa Inggeris. Berdasarkan hasil yang telah diperolehi, sistem ini berjaya mengsegmentasikan huruf-huruf tersebut dengan berkesan dan tepat.


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How to Cite

Za’bah, N. F., Muhammad Nazmi, A. A. A., & Azman, A. W. (2020). WORD SEGMENTATION OF OUTPUT RESPONSE FOR SIGN LANGUAGE DEVICES. IIUM Engineering Journal, 21(2), 153 - 163. https://doi.org/10.31436/iiumej.v21i2.1408



Electrical, Computer and Communications Engineering

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