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Application for Translating Speech to Gesture Language

Student: Davletshin Artur

Supervisor: Hadi Saleh

Faculty: Faculty of Computer Science

Educational Programme: System and Software Engineering (Master)

Year of Graduation: 2020

This paper is focused on development of an iOS mobile application intended for translating speech into sign language, which runs in real-time and requires no network connection to function properly as opposed to existing implementations. In addition to that, the application is scalable to support translation between culturally unrelated spoken and signed languages which is enabled by adoption of statistical machine translation thereby avoiding explicit knowledge of languages structure, whereas signed languages are represented textually using SignWriting notation. The application synthesizes signing gestures for translation results using an avatar. This application software design is based on a systematized knowledge of signed communication and inclusive software design challenges, natural language processing methods, and existing implementations analysis. The development methodology considers a limited budget, and mobile software development specificity. Therefore, this paper suggests an approach to a translator application design which can facilitate communication for the deaf and the others. This paper consists of 42 pages, 13 figures, 3 tables, and 76 references. Key words: sign language, speech recognition, machine translation, mobile application.

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