构建60万张克什米尔语文字图像数据集，助力濒危语言识别
600k-ks-ocr: a large-scale synthetic dataset for optical character recognition in kashmiri script
- 用合成方法生成60万张克什米尔语文字图像，适配多种识别模型
- 图像分辨率256x64，含真实文档退化模拟与背景纹理增强鲁棒性
- 专为低资源语言OCR设计，适合研究濒危语言数字化的学者
本文介绍600K-KS-OCR数据集，一个大规模合成语料库，包含约60.2万张单词级分割图像，用于训练和评估针对克什米尔语的光学字符识别系统。该语言属于使用改良波斯-阿拉伯字母的达迪克语系，约有七百万使用者，现处于濒危状态。每张图像尺寸为256x64像素，附带多格式真实转录文本，兼容CRNN、TrOCR及通用机器学习流程。生成方法融合三种传统克什米尔字体，通过数据增强模拟真实文档退化，并引入多样背景纹理以提升模型鲁棒性。数据集分为十个分区，总大小约10.6 GB，采用CC-BY-4.0许可发布，旨在推动低资源语言光学字符识别研究。
原文摘要 · Abstract (English)
This technical report presents the 600K-KS-OCR Dataset, a large-scale synthetic corpus comprising approximately 602,000 word-level segmented images designed for training and evaluating optical character recognition systems targeting Kashmiri script. The dataset addresses a critical resource gap for Kashmiri, an endangered Dardic language utilizing a modified Perso-Arabic writing system spoken by approximately seven million people. Each image is rendered at 256x64 pixels with corresponding ground-truth transcriptions provided in multiple formats compatible with CRNN, TrOCR, and generalpurpose machine learning pipelines. The generation methodology incorporates three traditional Kashmiri typefaces, comprehensive data augmentation simulating real-world document degradation, and diverse background textures to enhance model robustness. The dataset is distributed across ten partitioned archives totaling approximately 10.6 GB and is released under the CC-BY-4.0 license to facilitate research in low-resource language optical character recognition.
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