By Izzath Nisfer, Ashini Kavindya, Ovindu Atukorala, Purushoth Velayuthan, Menan VelayuthanSource:
arXiv cs.CLarXiv:2607.22456v1 Announce Type: new Abstract: Existing lexical distance, similarity, and
evaluationmetrics 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.Get AI news in your inbox
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