Deepsign: Sign Language Detection and Recognition Using Deep Learning
Charotar University of Science and Technology · Universidad de Salamanca · +2 more institutions
Abstract
The predominant means of communication is speech; however, there are persons whose speaking or hearing abilities are impaired. Communication presents a significant barrier for persons with such disabilities. The use of deep learning methods can help to reduce communication barriers. This paper proposes a deep learning-based model that detects and recognizes the words from a person’s gestures. Deep learning models, namely, LSTM and GRU (feedback-based learning models), are used to recognize signs from isolated Indian Sign Language (ISL) video frames. The four different sequential combinations of LSTM and GRU (as there are two layers of LSTM and two layers of GRU) were used with our own dataset, IISL2020. The…
Citation impact
- FWCI
- 24.11
- Percentile
- 100%
- References
- 26
Authors
6- DKDeep KothadiyaCorresponding
Charotar University of Science and Technology
- CBChintan BhattCorresponding
Charotar University of Science and Technology
- KSKrenil Sapariya
Charotar University of Science and Technology
- KPKevin Patel
Charotar University of Science and Technology
- ABAna Belén Gil González
Universidad de Salamanca
Topics & keywords
- Sign language
- Gesture
- Computer science
- Deep learning
- Speech recognition
- Sign (mathematics)
- Artificial intelligence
- American Sign Language
- Quality Education