Current Trends in Developing Parallel Corpora for Text-to-Sign Language Translation
Fragment książki (Rozdział monografii pokonferencyjnej)
MNiSW
5
spoza wykazu
| Status: | |
| Autorzy: | Amangeldy Nurzada, Miłosz Marek, Yerimbetova Aigerim, Tursynova Nazira, Kurmetbek Bekbolat, Gazizova Nazerke |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Strony: | 135 - 144 |
| Scopus® Cytowania: | 0 |
| Bazy: | Scopus |
| Efekt badań statutowych | NIE |
| Finansowanie: | Sincere gratitude is expressed to all those who provided invaluable support throughout this research. Special thanks to the subproject \u201C62755-Development of a Virtual Sign Language Interpreter in Kazakh Sign Language for Hearing-Impaired Users, \u201D funded under the \u201CStimulating Productive Innovation\u201D project, supported by the World Bank and the Government of the Republic of Kazakhstan. Funding. This research was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR24992875). |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | First International Conference on Computational Intelligence in Engineering Science |
| Skrócona nazwa konferencji: | 1st ICCIES 2025 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 23 lipca 2025 do 25 lipca 2025 |
| Miasto konferencji: | Ho Chi Minh City |
| Państwo konferencji: | WIETNAM |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| This article presents a review of modern approaches to creating parallel corpora for sign language machine translation, including data collection and annotation, synchronization of texts and video recordings, training models based on deep neural networks and transformers, and evaluating translation quality using standard metrics. As part of the study, a parallel corpus consisting of 998 sentences and over 5,000 words was developed, incorporating both manually generated and authentic texts from school textbooks. Particular attention is paid to analyzing technologies such as synthetic data generation, the application of multimodal features, and gesture visualization using 3D avatars. The primary goal of the study is to identify optimal strategies for creating corpora that account for the unique characteristics of sign languages and the limited availability of annotated data, thereby paving the way for the development of highly accurate machine translation systems that enhance information accessibility for deaf and hard-of-hearing individuals. |
