Nazerke Kalidolda
ABSTRACT
Hearing-impaired communities around the world communicate via a sign language. The focus of this work is to develop an interpreting human-robot interaction system that could act as a sign language interpreter in public places. To this end, we utilize a number of technologies including depth cameras (a leap motion sensor and Microsoft Kinect), humanoid robots NAO and Pepper, and deep learning approaches for classification.
Supplemental Material
- Nazgul Tazhigaliyeva, Nazerke Kalidolda, Alfarabi Imashev, Shynggys Islam, Kairat Aitpayev, German I Parisi, and Anara Sandygulova . 2017. Cyrillic manual alphabet recognition in RGB and RGB-D data for sign language interpreting robotic system (SLIRS). In Robotics and Automation (ICRA), 2017 IEEE International Conference on. IEEE, 4531--4536.Google Scholar
Digital Library
Index Terms
- Towards Sign Language Interpreting Robotic System
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