POS Tagging on Handwritten Sindhi Sentences

This dataset consists of high-resolution images of handwritten Sindhi sentences, meticulously curated for tasks such as Part-of-Speech (POS) tagging and Named Entity Recognition (NER). The dataset aims to facilitate research and development in natural language processing (NLP) and optical character recognition (OCR) for low-resource languages like Sindhi. Key Features: Language: Sindhi (script-based with unique linguistic characteristics). Dataset Size: Contains 1000+ labeled images with diverse handwriting styles. Annotations: Each image is manually annotated for POS tagging and NER tasks, ensuring high accuracy. Applications: Suitable for training and evaluating machine learning models in NLP, OCR, and language understanding. Diversity: Includes variations in sentence length, word structure, and handwriting styles to mimic real-world scenarios.