Koshur Pixel: a large-scale synthetic ocr dataset for kashmiri

• URL: http://arxiv.org/abs/2606.23144v1
• Date: Mon, 22 Jun 2026 10:42:36 GMT
• Title: Koshur Pixel: a large-scale synthetic ocr dataset for kashmiri
• Abstract summary: We introduce Koshur Pixel, the first large-scale synthetic OCR dataset for Kashmiri.<n>Koshur Pixel comprises 613,078 image-text pairs generated from the KS-PRET-5M corpus using the SynthOCR-Gen framework.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Optical Character Recognition (OCR) for low-resource languages is often constrained by the lack of annotated training data and the complexity of script-specific rendering. Kashmiri, written primarily in the Perso-Arabic Nastaliq script, presents additional challenges due to contextual glyph shaping, dense ligatures, and orthographic variability. We introduce Koshur Pixel, the first large-scale synthetic OCR dataset for Kashmiri, comprising 613,078 image-text pairs generated from the KS-PRET-5M corpus using the SynthOCR-Gen framework. The dataset spans multiple fonts and textual granularities, ranging from individual words to full-page documents, and incorporates more than 25 augmentation strategies that emulate real-world document degradations. Koshur Pixel provides a scalable and cost-effective alternative to manual annotation, establishing a foundational resource for training OCR systems, digitizing Kashmiri textual heritage, and advancing language technologies for a severely under-resourced language.

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