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标注词（gloss）构建，经精心打造以提升印度手语（Indian Sign Language，ISL）手势识别与生成系统的精度与鲁棒性。我们公开本数据集的初衷，是为科研社区贡献一份宝贵资源，助力同行研究者在手语识别与生成领域开展探索与创新。数据集概览：本数据集涵盖丰富多样的印度手语手势视频与标注词数据集。本语境中“标注词（gloss）”通常指对手语手势含义的书面或口头描述，可实现手语的书面化表征。数据集包含各手势对应的口语/书面语言信息，以及各手势的标注词。手语标注词数据集的核心组成部分包括：采用分层架构的印度手语语法，融入了用于表示时态的专属空间索引，以及包含复合词的词库；其遵循独特的语序规则，可适配名词、动词、宾语、形容词或疑问词成分。马拉地手语采用主-宾-谓（SOV）语序，便于理解且适配区域语言场景。本马拉地手语标注词旨在成为听障群体日常沟通的媒介。本数据集经过严谨的筛选与整理流程，模拟真实应用场景：原始视频由专业手语表演者录制，涵盖了丰富多样的手语手势表达；拍摄采用绿幕背景与可控光照条件，以增强数据真实性。本数据集所有视频均采用统一像素规格，保障数据展示的一致性，同时可简化预处理与模型开发环节；视频存储格式兼容各类机器学习与深度学习框架，能够无缝融入科研研发管线。

搜集汇总

背景与挑战

背景概述

ISLVT是一个专注于印度手语句子级别的视频和文本数据集，包含76个英语-马拉地语-ISL gloss句子对和152个高质量视频（正面和侧面视图），总大小2.56 GB。数据集旨在提升ISL手势识别和生成系统的精度，模拟真实场景，由专业手语者表演，并采用绿屏和受控光照以确保一致性，遵循ISL语法和SOV词序，兼容多种机器学习框架。