Abstract
Sign language recognition has attracted the interest of researchers in recent years. While numerous approaches have been proposed for European and Asian sign languages recognition, very limited attempts have been made to develop similar systems for the Arabic sign language (ArSL). This can be attributed partly to the lack of a dataset at the sentence level. In this paper, we aim to make a significant contribution by proposing ArabSign, a continuous ArSL dataset. The proposed dataset consists of 9,335 samples performed by 6 signers. The total time of the recorded sentences is around 10 hours and the average sentence's length is 3.1 signs. ArabSign dataset was recorded using a Kinect V2 camera that provides three types of information (color, depth, and skeleton joint points) recorded simultaneously for each sentence. In addition, we provide the annotation of the dataset according to ArSL and Arabic language structures that can help in studying the linguistic characteristics of ArSL. To benchmark this dataset, we propose an encoder-decoder model for Continuous ArSL recognition. The model has been evaluated on the proposed dataset, and the obtained results show that the encoder-decoder model outperformed the attention mechanism with an average word error rate (WER) of 0.50 compared with 0.62 with the attention mechanism. The data and code are available at https://github.com/Hamzah-Luqman/rabSign
Original language | English |
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Title of host publication | 2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition, FG 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350345445 |
DOIs | |
State | Published - 2023 |
Event | 17th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2023 - Waikoloa Beach, United States Duration: 5 Jan 2023 → 8 Jan 2023 |
Publication series
Name | 2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition, FG 2023 |
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Conference
Conference | 17th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2023 |
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Country/Territory | United States |
City | Waikoloa Beach |
Period | 5/01/23 → 8/01/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence
- Computer Vision and Pattern Recognition