# On the Non-Specificity of Statistical Measures Used in Script Decipherment

arXiv: https://arxiv.org/abs/2608.02999 · HTML: https://mlsanity.com/paper/2608.02999/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 64 references that are in the map.
- First posted on arXiv 4 Aug 2026.

## Builds on (most cited first, 2 of 2)

- [Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B](https://mlsanity.com/paper/1906.06718/) (2019)
- [The "handedness" of language: Directional symmetry breaking of sign usage in words](https://mlsanity.com/paper/1509.09121/) (2015)

## Abstract (arXiv)

Statistical regularities are routinely offered as evidence that undeciphered sign systems encode language; the Indus script debate is the canonical example. Any such inference rests on specificity: the reported outcome must be unusual among plausible structured non-languages. We test that premise constructively with SIGIL, a purpose-built generative emblem system whose 3,000-text core corpus carries explicit compositional meanings although no sign has a phonological value. A literature registry compiled in advance of evaluation records 54 methods and admits a method to exact scoring when both the published Indus outcome and a source-defined decision rule can be reproduced. SIGIL receives the same category as the Indus corpus on every criterion scored this way, across repetition, directional-asymmetry, and lexical-distribution tests. Declared reconstructions of entropy, frequency, positional, predictive, classifier, and network measures reproduce the familiar Indus-like signatures as well. A sequential decipherment stress test then reaches high dictionary coverage for English, Sanskrit, and Tamil on the same corpus, while grouped held-out declines and unstable keys reveal how little that coverage identifies. The construction does not decide what the Indus signs encode: it shows that the evaluated measures detect organization without being specific to language, and therefore cannot, on their own, establish encoded speech.