Automatic transformation of Kazakh text into sign language glosses using multilingual transformer-based models
This study investigates the automatic transformation of Kazakh text into sign language glosses (Text-to-Gloss) using multilingual transformer-based models with emphasis on preserving morphological structure in a low-resource agglutinative language framework. Given the scarcity of high-quality intermediate representations for Kazakh Sign Language, a methodology for corpus formation was developed, resulting in a specialized dataset of 11 190 unique text−gloss pairs sourced from educational materia
Record details
Published: 7 August 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Finance, VC & PE
Retrieved: 8 August 2026
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ethics.ai (7 August 2026), “Automatic transformation of Kazakh text into sign language glosses using multilingual transformer-based models,” evidence record 17497, https://ethics.ai/record/17497 (originally published by Frontiers in Artificial Intelligence).
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