Indian Sign Language Video and Text dataset for sentences (ISLVT)

This video and gloss-based dataset has been meticulously crafted to enhance the precision and resilience of ISL (Indian Sign Language) gesture recognition and generation systems. Our goal in sharing this dataset is to contribute to the research community, providing a valuable resource for fellow researchers to explore and innovate in the realm of sign language recognition and generation.Overview of the Dataset: Comprising a diverse array of ISL gesture videos and gloss datasets. The term "gloss" in this context often refers to a written or spoken description of the meaning of a sign, allowing for the representation of sign language in a written form. The dataset includes information about the corresponding spoken or written language and the gloss for each sign. Key components of a sign language gloss dataset include ISL grammar that follows a layered approach, incorporating specific spatial indices for tense and a lexicon with compounds. It follows a unique word order based on noun, verb, object, adjective, or part of a question. Marathi sign language follows the subject-object-verb (SOV) form, facilitating comprehension and adaptation to regional languages. This Marathi sign language gloss aims to become a medium for everyday communication among deaf individuals. This dataset reflects a careful curation process, simulating real-world scenarios. The original videos showcase a variety of gestures performed by a professional signer capturing a broad spectrum of sign language expressions. Incorporating Realism with green screen with controlled lighting conditions. All videos within this dataset adhere to pixels, ensuring uniformity for data presentation and facilitating streamlined pre-processing and model development stored in a format compatible with various machine and Deep learning frameworks, these videos seamlessly integrate into the research pipeline

本数据集基于视频与gloss（gloss）精心构建，旨在提升印度手语（Indian Sign Language，ISL）手势识别与生成系统的精度及鲁棒性。我们共享该数据集的目标是为研究社区贡献力量，为同行研究者提供宝贵资源，助力其在手语识别与生成领域开展探索与创新。

数据集概述：包含多样化的ISL手势视频与gloss数据集。本语境中的"gloss"通常指对sign（sign）含义的书面或口头描述，使手语能够以书面形式呈现。数据集包含每个sign对应的口语或书面语信息及gloss。手语gloss数据集的核心组件包括采用分层方法的ISL语法（融入时态特定空间索引）以及含复合词的词汇表。其遵循基于名词、动词、宾语、形容词或疑问句成分的独特词序。马拉地手语采用主-宾-谓（Subject-Object-Verb，SOV）结构，便于理解及向区域语言的适配。该马拉地手语gloss旨在成为听障人士日常交流的媒介。本数据集体现了严谨的精选过程，模拟真实场景。原始视频展示了专业手语者表演的多种手势，捕捉了广泛的手语表达谱。通过绿幕与受控光照条件增强真实感。数据集中所有视频均遵循像素标准，确保数据呈现的一致性，促进高效预处理与模型开发；视频以兼容各类机器学习及深度学习框架的格式存储，可无缝融入研究流程（pipeline）。