Abstract
There are around 50-100 thousand deaf people in Poland, their main language is Polish sign language. It can be challenging for them to communicate with the rest of society and there is a gap in Polish sign language gestures to text conversion. Although some research has been done before, no research paper or product solves this problem. The primary objective is to develop a concept of an intelligent application that can convert Polish sign language from either a video or a live feed. To achieve this, research was conducted on other sign languages, which helped in selecting the most promising hybrid models of deep neural networks. Subsequently, tests were conducted and the best model was chosen. Finally, the best model was trained on the dataset of Polish sign language, using weights (transfer learning) trained on the MS American Sign Language dataset.
Paper Type
Short Paper
DOI
10.62036/ISD.2024.88
Polish Sign Language Gestures to Text Conversion Using Machine Learning
There are around 50-100 thousand deaf people in Poland, their main language is Polish sign language. It can be challenging for them to communicate with the rest of society and there is a gap in Polish sign language gestures to text conversion. Although some research has been done before, no research paper or product solves this problem. The primary objective is to develop a concept of an intelligent application that can convert Polish sign language from either a video or a live feed. To achieve this, research was conducted on other sign languages, which helped in selecting the most promising hybrid models of deep neural networks. Subsequently, tests were conducted and the best model was chosen. Finally, the best model was trained on the dataset of Polish sign language, using weights (transfer learning) trained on the MS American Sign Language dataset.
Recommended Citation
Lemieszewski, Ł., Nowak, M. & Becker, J. (2024). Polish Sign Language Gestures to Text Conversion Using Machine Learning. In B. Marcinkowski, A. Przybylek, A. Jarzębowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gdańsk, Poland: University of Gdańsk. ISBN: 978-83-972632-0-8. https://doi.org/10.62036/ISD.2024.88