SyriSign: A Parallel Corpus for Arabic Text to Syrian Arabic Sign Language Translation

1. 1Collect and annotate a large dataset of video samples for Syrian Arabic Sign Language
2. 2Develop and fine-tune machine learning models for Arabic text to SyArSL translation using the SyriSign corpus
3. 3Evaluate the performance of the models on the SyriSign dataset and compare with other state-of-the-art models
4. 4Explore applications of the SyriSign corpus in real-world scenarios, such as sign language recognition and generation

AI engineers and researchers working on sign language translation and low-resource languages can benefit from this dataset, as it provides a valuable resource for training and testing models

💡 The SyriSign corpus addresses the lack of resources for low-resource sign languages like Syrian Arabic Sign Language, enabling the development of more accurate and effective sign language translation models

📚 Introducing SyriSign, a new parallel corpus for Arabic text to Syrian Arabic Sign Language translation! 💻