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The Iterative Development and Evaluation Framework for Kazakh-Russian Signing Avatars Targeted to Native Deaf Signers

Nowadays, existing research predominantly focuses on already well-researched sign languages. However, the most extensive studies of sign language in Kazakhstan, which adhere to international standards, started about a decade ago. Native deaf signers in Kazakhstan can often suffer from insufficient educational opportunities, which may result in limited reading proficiency too. Sometimes, deaf signers can recognize letters and read words, but they may not fully understand the overall concept and need to break it down into a sequence of simpler ideas to comprehend it better. Consequently, signing avatars have the potential to interpret internet statements, movie subtitles, or YouTube videos, and this sign language production may increase accessibility and improve communication between deaf and hearing individuals, as well as between humans and avatars. An equally critical challenge is how to develop a tool that will help deaf signers evaluate the performance, appearance, and naturalness of signing avatars without relying on written text across all sign languages, particularly in underserved communities. This paper outlines the iterative development of the Kazakh-Russian Sign Language interpreting avatar, ongoing improvements to the evaluation instrument, and a comparative analysis of this instrument with another evaluation method designed to attain the same objective.