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Sign language is an essential communication tool for those who are deaf or hearing impaired. This study offers a thorough analysis of current developments in methods for computer vision and deep learning for Sign Language Translation (SLT) systems. We investigate several approaches, such as CNNs and LSTM networks, and their application to different sign languages, such as Indian Sign Language (ISL). Significant topics are discussed, including the requirement for large datasets, the ability to translate in real- time, and the incorporation of multimodal inputs. The study also highlights the possibilities of hybrid approaches and investigates how they might be used to close communication gaps. Finally, it provides the mathematical underpinnings and real-world applications of these strategies. The review aims to offer perspectives on contemporary methods and future directions for improving SLT systems.

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Evaluating Sign Language Translation Methodologies for the Specially Abled Community

  • 会议论文

  • 发表日期：

    2026年

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  • S. Pramila,
  • Asha Rani Borah,
  • Soham Mondal,
  • Vansh Vidyarthy,
  • Adnan Aadil Burhan,
  • Naman Singhal

摘要

Sign language is an essential communication tool for those who are deaf or hearing impaired. This study offers a thorough analysis of current developments in methods for computer vision and deep learning for Sign Language Translation (SLT) systems. We investigate several approaches, such as CNNs and LSTM networks, and their application to different sign languages, such as Indian Sign Language (ISL). Significant topics are discussed, including the requirement for large datasets, the ability to translate in real- time, and the incorporation of multimodal inputs. The study also highlights the possibilities of hybrid approaches and investigates how they might be used to close communication gaps. Finally, it provides the mathematical underpinnings and real-world applications of these strategies. The review aims to offer perspectives on contemporary methods and future directions for improving SLT systems.