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grapheme-kit: Grapheme-Level Metrics and Text Processing for Multilingual NLP

2026-07-24 16:14:37
Izzath Nisfer, Ashini Kavindya, Ovindu Atukorala, Purushoth Velayuthan, Menan Velayuthan
arXiv_CL
   
Abstract

Existing lexical distance, similarity, and evaluation metrics operate on Unicode code points, which can misrepresent errors in writing systems where a single grapheme is represented by multiple Unicode code points. We introduce grapheme-kit, an open-source Python library that extends these metrics to operate on grapheme clusters instead. The library also provides improved grapheme processing for Tamil and Sinhala, including accurate grapheme cluster identification and grapheme composition/decomposition utilities. Through an OCR case study, we demonstrate that grapheme-level metrics provide a more faithful evaluation of complex scripts.

Abstract (translated)

URL

https://arxiv.org/abs/2607.22456

PDF

https://arxiv.org/pdf/2607.22456.pdf

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