How Non-Linguistic Is the Indus Sign System? A Synthetic-Baseline Scorecard

TL;DR

This study evaluates whether the Indus sign system exhibits linguistic properties by comparing it to non-linguistic baselines, revealing it does not fully match either, suggesting a complex nature.

Contribution

Introduces a multi-metric framework to assess linguistic versus non-linguistic features in the Indus corpus, providing a novel quantitative analysis.

Findings

Indus corpus does not match either non-linguistic baseline.

Indus signs occupy an intermediate position between the two baselines.

No real-world non-linguistic corpus fully reproduces Indus statistical profile.

Abstract

Whether the Indus Valley sign system (c. 2600-1900 BCE) encodes spoken language has been debated for decades. This paper introduces a multi-metric discrimination framework that tests the observed Indus corpus against two kinds of computer-generated non-linguistic baseline -- one mimicking a heraldic emblem system, the other an administrative coding system -- each calibrated with Zipfian frequency distributions, positional constraints, and bigram dependencies derived from six attested non-linguistic corpora. The scorecard evaluates four properties central to the Farmer-Sproat-Witzel (2004) critique: text brevity, repeated formulaic phrases, hapax legomenon rate, and positional rigidity. Applying this framework to 1,916 deduplicated inscriptions (584 unique signs, 11,110 tokens) from the ICIT/Yajnadevam digitization, we find that the Indus corpus does not match either baseline cleanly. Across the four metrics examined, the Indus corpus occupies an intermediate position relative to the two baseline families, matching neither cleanly. Neither a heraldic nor an administrative generator can reproduce all four properties at once. We also compare against seven real-world non-linguistic corpora including Sproat's (2014) datasets, finding that no attested non-linguistic system reproduces the full Indus statistical profile either. We replicate key prior results including a Zipf slope of -1.49 and conditional entropy of 3.23 bits. All code and data are publicly available.