mlsanityData to 14 Oct 2026

Clarifying orthography: Orthographic transparency as compressibility

arXiv 2505.13657 ↗First posted 19 May 2025cs.CL cs.IT math.ITcited by 1

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Abstract (arXiv)

Orthographic transparency -- how directly spelling is related to sound -- lacks a unified, script-agnostic metric. Using ideas from algorithmic information theory, we quantify orthographic transparency in terms of the mutual compressibility between orthographic and phonological strings. Our measure provides a principled way to combine two factors that decrease orthographic transparency, capturing both irregular spellings and rule complexity in one quantity. We estimate our transparency measure using prequential code-lengths derived from neural sequence models. Evaluating 22 languages across a broad range of script types (alphabetic, abjad, abugida, syllabic, logographic) confirms common intuitions about relative transparency of scripts. Mutual compressibility offers a simple, principled, and general yardstick for orthographic transparency.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 28 references that are in the map. First posted on arXiv 19 May 2025.

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2 of 28 references.

References · 2

  1. 2017Convolutional Sequence to Sequence Learningcited by 552
  2. 2018The Description Length of Deep Learning Modelscited by 72

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