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

• URL: http://arxiv.org/abs/2604.17828v1
• Date: Mon, 20 Apr 2026 05:29:56 GMT
• Title: How Non-Linguistic Is the Indus Sign System? A Synthetic-Baseline Scorecard
• Abstract summary: This paper introduces a multi-metric discrimination framework to test whether the Indus Valley sign system encodes spoken language.<n>Applying this framework to 1,916 deduplicated inscriptions from the ICIT/Yajnadevam digitization, we find that the Indus corpus does not match either baseline cleanly.<n>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.
• Score: 0.913755431537592
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

Related papers

• Neyshekar: An Open Persian Read-Speech Corpus for Automatic Speech Recognition [0.0]
  Neyshekar is an open Persian read-speech corpus designed for coverage of both formal and informal language.<n>In version 6, 62,279 validated recordings totalling 99.02 hours are provided from 190 contributors, with 34,541 distinct recorded prompts.
  arXiv  Detail & Related papers  (2026-09-13T14:30:43Z)
• IndicQE-APE: A Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages [77.88427845181154]
  We consolidate the WMT 2020--2024 shared-task lineage with an extended English--Malayalam resource into indicqe: $126,754$ instances over nine directional pairs.<n>We benchmark six prompted LLMs and three COMET metrics on segment-level QE, and three systems on APE.
  arXiv  Detail & Related papers  (2026-08-17T09:50:52Z)
• On the Non-Specificity of Statistical Measures Used in Script Decipherment [0.0]
  SIGIL is a purpose-built generative emblem system whose 3,000-text core corpus carries explicit compositional meanings.<n>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.<n> SIGIL receives the same category as the Indus corpus on every criterion scored this way, across repetition, directional-asymmetry, and lexical-distribution tests.
  arXiv  Detail & Related papers  (2026-08-04T01:33:02Z)
• Fantastic Adaptive Taxonomies and How to Use Them [100.20614173157708]
  AdaMAST converts execution traces into a compact, evidence-grounded failure taxonomy.<n>No code is hand-authored, no trace human-annotated.<n>In agent-system search, taxonomy-coded diagnoses of failed candidates outperform free-form.
  arXiv  Detail & Related papers  (2026-07-17T17:41:16Z)
• ITPEval: Benchmarking Formal Translation Across Interactive Theorem Provers [77.95933562142014]
  ITPEval is the first benchmark for evaluating automated formal proof translation across four major ITPs.<n>We release itpeval, a unified multi-ITP verification infrastructure with state-isolated warm backends.
  arXiv  Detail & Related papers  (2026-07-07T22:05:55Z)
• Structural Pattern Mining in Inka Khipus: Unsupervised Clustering, Provenance Classification, and a Computational Validation of the Santa Valley Match [0.0]
  We present a machine-learning pipeline applied to the Open Khipu Repository (OKR), a public database of 619 khipus comprising 54,403 cords and 110,677 knots.<n>We engineer 27 structural features per khipu and apply (i) unsupervised clustering via UMAP and HDBSCAN, recovering three structurally distinct groups.<n>We report a negative result: reproducing knot-type sequence order, encoded as n-grams, adds no signal beyond aggregate features.
  arXiv  Detail & Related papers  (2026-06-30T21:06:38Z)
• Invisible to humans, visible to machines: a preregistered audit of Unicode fidelity across four biomedical bibliographic APIs [0.0]
  This audit tests that assumption for four widely used public APIs (E-utilities, Crossref, OpenAlex, Semantic Scholar) against PubMed Central (PMC) JATS XML as a common ground truth.<n>Character-level fidelity is therefore API-dependent and undocumented, with direct consequences for tokenization-sensitive bibliometrics, corpus construction, and character-level indicators of LLM-assisted writing.
  arXiv  Detail & Related papers  (2026-06-08T19:46:27Z)
• Benchmarking Speech-to-Speech Translation Models [55.00303727199927]
  Speech-to-speech translation (S2ST) has advanced rapidly, but offline evaluation lacks a unified protocol.<n>We introduce a benchmarking framework integrating 46 metrics across eight dimensions.<n>We deploy it on 1,248 model-language configurations from FLEURS and CVSS.
  arXiv  Detail & Related papers  (2026-06-02T07:01:33Z)
• Not All Synthetic Data Is Yours to Learn From [68.13136636413601]
  We show that weak self-training can amplify capabilities already present in the pretrained model.<n>We study this in the minimal setting of prompt-free unconditional self-training.
  arXiv  Detail & Related papers  (2026-05-29T10:34:11Z)
• Synthetic Tabular Generators Fail to Preserve Behavioral Fraud Patterns: A Benchmark on Temporal, Velocity, and Multi-Account Signals [0.0]
  We formalize a taxonomy of four behavioral fraud patterns (P1-P4) covering inter-event timing, burst structure, multi-account graph motifs, and velocity-rule trigger rates.<n>We benchmark CTGAN, TVAE, GaussianCopula, and TabularARGN on IEEE-CIS Fraud Detection and the Amazon Fraud dataset.<n>The P1-P4 framework extends to any domain with entity-level sequential data, including healthcare and network security.
  arXiv  Detail & Related papers  (2026-04-13T19:36:00Z)
• Evidence of Layered Positional and Directional Constraints in the Voynich Manuscript: Implications for Cipher-Like Structure [0.0]
  We present a systematic analysis of the Voynich Manuscript (VMS)<n>The VMS exhibits cipher-like structural constraints that are difficult to reproduce from simple positional or frequency-based mechanisms alone.
  arXiv  Detail & Related papers  (2026-03-26T14:01:19Z)
• Reconstructing Trust Embeddings from Siamese Trust Scores: A Direct-Sum Approach with Fixed-Point Semantics [0.0]
  We study the inverse problem of reconstructing high-dimensional trust embeddings from the one-dimensional Siamese trust scores that many distributed-security frameworks expose.<n>A suite of synthetic benchmarks confirms that, even in the presence of Gaussian noise, the recovered embeddings preserve inter-device geometry as measured by Euclidean and cosine metrics.<n>The paper demonstrates a practical privacy risk: publishing granular trust scores can leak latent behavioural information about both devices and evaluation models.
  arXiv  Detail & Related papers  (2025-08-02T20:19:22Z)
• The Medium Is Not the Message: Deconfounding Document Embeddings via Linear Concept Erasure [98.71456610527598]
  Embedding-based similarity metrics can be influenced by spurious attributes like the text's source or language.<n>This paper shows that a debiasing algorithm that removes information about observed confounders from the encoder representations substantially reduces these biases at a minimal computational cost.
  arXiv  Detail & Related papers  (2025-07-01T23:17:12Z)
• ToxSyn-PT: A Large-Scale Synthetic Dataset for Hate Speech Detection in Portuguese [37.69303106863453]
  ToxSyn-PT is the first large-scale Portuguese corpus that enables fine-grained hate-speech classification.<n>The dataset contains 53,274 synthetic sentences equally distributed between minorities groups and toxicity labels.
  arXiv  Detail & Related papers  (2025-06-11T23:59:29Z)
• LipSim: A Provably Robust Perceptual Similarity Metric [56.03417732498859]
  We show the vulnerability of state-of-the-art perceptual similarity metrics based on an ensemble of ViT-based feature extractors to adversarial attacks. We then propose a framework to train a robust perceptual similarity metric called LipSim with provable guarantees. LipSim provides guarded areas around each data point and certificates for all perturbations within an $ell$ ball.
  arXiv  Detail & Related papers  (2023-10-27T16:59:51Z)
• Detecting Handwritten Mathematical Terms with Sensor Based Data [71.84852429039881]
  We propose a solution to the UbiComp 2021 Challenge by Stabilo in which handwritten mathematical terms are supposed to be automatically classified. The input data set contains data of different writers, with label strings constructed from a total of 15 different possible characters.
  arXiv  Detail & Related papers  (2021-09-12T19:33:34Z)
• A New Approach for Texture based Script Identification At Block Level using Quad Tree Decomposition [38.20489458130109]
  In a country like India, where multi-script scenario is prevalent, identifying scripts beforehand becomes obligatory. We present the significance of Gabor wavelets filters in extracting directional energy and entropy distributions for 11 official handwritten scripts.
  arXiv  Detail & Related papers  (2020-09-16T02:50:03Z)
• Sparse Concept Coded Tetrolet Transform for Unconstrained Odia Character Recognition [0.0]
  We propose a new image representation approach for unconstrained alphanumeric characters using sparse concept coded Tetrolets. The proposed OCR system is shown to perform better than other sparse based techniques such as PCA, SparsePCA and Slantlet.
  arXiv  Detail & Related papers  (2020-04-03T13:20:12Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.