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This study critically evaluates the specificity of statistical measures used in deciphering undeciphered scripts, particularly the Indus script, by employing SIGIL, a generative emblem system with 3,000 texts that convey explicit meanings without phonological values. Through a comprehensive evaluation using 54 methods, the authors demonstrate that SIGIL's statistical signatures closely resemble those attributed to the Indus corpus, suggesting that these measures can indicate organization without confirming linguistic encoding. The findings highlight that while statistical regularities may suggest language-like properties, they are insufficient to definitively establish the presence of encoded speech in undeciphered scripts.
Statistical measures that claim to identify language in undeciphered scripts may merely reflect organizational patterns, not linguistic content.
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.
