Title
Polish Sign Language Gestures to Text Conversion Using Machine Learning
Authors
[ 1 ] Wydział Techniczny, Akademia im. Jakuba z Paradyża | [ P ] employee
Scientific discipline (Law 2.0)
Year of publication
2024
Chapter type
chapter in monograph / paper
Publication language
english
Keywords
EN
- Machine Learning (ML)
- Convolution Networks (CN)
- Sequence data classification
- Sign Language (SL)
Abstract
EN 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
Date of online publication
2024
Pages (from - to)
1 - 8
Ministry points / chapter
20
Ministry points / conference (CORE)
140
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