grapheme-kit: Grapheme-Level Metrics and Text Processing for Multilingual NLP
Izzath Nisfer, Ashini Kavindya, Ovindu Atukorala, Purushoth Velayuthan, Menan Velayuthan
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.
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Classified with taxonomy v2 on Sat, 5 Sept 2026.