Abstract
This paper presents a new data collection tool for sign language recognition with Leap Motion Controller. The main motivation of this study is to develop assistive technology in order to support hearing-impaired people. This study is a part of RoboRehab project where we aim to develop an affectively aware robotic rehabilitation platform to assist hearing-impaired children in hospitals. The tool is cost efficient and has a simple and user-friendly interface design. The study involves a set of 12 dynamic two-handed signs (words) from Turkish Sign Language (TID).
| Original language | English |
|---|---|
| Title of host publication | Springer Series in Design and Innovation |
| Publisher | Springer Nature |
| Pages | 353-361 |
| Number of pages | 9 |
| DOIs | |
| Publication status | Published - 2021 |
Publication series
| Name | Springer Series in Design and Innovation |
|---|---|
| Volume | 13 |
| ISSN (Print) | 2661-8184 |
| ISSN (Electronic) | 2661-8192 |
Bibliographical note
Publisher Copyright:© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
- Assistive technology
- Data processing
- Deep learning
- Human–machine interaction
- Leap motion
- Machine learning
- Sign language
- Sign recognition