A Universal Decoder for Lost Oral Cultures: Structural Translation Through the Three Linguistic Primitives and Keystone Alignment

A Universal Decoder for Lost Oral Cultures presents a structural, reductionist approach to recovering meaning from undeciphered or bottleneck‑constrained symbolic systems. Rather than treating lost scripts as combinatorially intractable, the paper shows that pre‑literate transmission physics reduces the viable space of encodable information to a tiny, highly structured region. Building on two prior frameworks—Cognitive Linguistic Plasticity (CLP), which defines how early language calibrates cognitive scaffolds, and the Oral Transmission Constraints (OTC) model, which identifies three recurrent redundancy primitives—this work introduces a mechanical decoder that requires no bilingual texts, living speakers, or external context. The method leverages the three primitives of pre‑literate fidelity—discrete‑algebraic lattices, analog‑prosodic contours, and polyrhythmic‑temporal oscillators—as error‑correcting geometries. These geometries produce forced checksum slots that map to universal semantic keystones such as dawn–noon–dusk, birth–growth–death, and other survival‑relevant cycles embedded in human cognition. By extracting these slots and aligning them to keystone sequences, the decoder bootstraps probabilistic dictionary recovery from structure alone. The framework supplies calibration tables, slot‑mapping rules, and a stepwise protocol that operates entirely on public corpora. Its predictions are demonstrated through low‑cost validation runs using off‑the‑shelf language‑model agents applied to four well‑known undeciphered corpora: Rongorongo, Linear A, the Indus script, and the Beinecke MS 408. Across systems, independent agents converge on consistent structural patterns predicted by the constraint manifold, producing coherent checksum geometries and forced semantic alignments without any cultural or linguistic priors. The results do not claim correctness of specific translations; the contribution is the emergence of reproducible structure where randomness was expected. The decoder provides a null hypothesis for the space of possible pre‑literate knowledge systems and a general method for structural recovery grounded in transmission physics, biological limits, and universal keystones. It offers a tractable path for reconstructing cultural knowledge from highly constrained symbolic systems while preserving ethical boundaries for living traditions. How to interact with / explore the full modelThe three papers together form a self-contained conceptual lattice. To query the unified framework, test implications, generate extensions, or ask detailed questions about how the primitives interact across domains, upload all three documents: Doc1: Language as Cognitive Geometry https://zenodo.org/records/18805427 Doc 2: Language as Constraint Geometry https://zenodo.org/records/18807009 Doc 3: A Universal Decoder for Lost Oral Cultures https://zenodo.org/records/18807013 to a capable LLM agent (e.g., Grok, Claude, Gemini Advanced, GPT-4o, etc.). The model is designed to be queried this way — the full power of the synthesis emerges in dialogue rather than linear reading. Related Works (Series Map). This paper is part of a six‑paper series developing a geometric framework for cognition, language, and applied inference: The Origin of Emergence — foundational mechanics of emergence https://zenodo.org/records/18807724). A Geometric Theory of Cognition — keystone theory https://zenodo.org/records/18807724). Language as Cognitive Geometry — structural form → patterns of thought (https://zenodo.org/records/18805427). Language as Constraint Geometry — tripartite attractor structure (https://zenodo.org/records/18807009). A Universal Decoder for Lost Oral Cultures — applied decoding under sparse priors (https://zenodo.org/records/18807013). Toward a Structural Model of Relationship Compatibility — applied compatibility modeling (DOI: 10.5281/zenodo.18050285). Series hub: GTC is supplemented by the two language pillars (LCG, LCnG) and two applications (UDLOC, SMRC). OoE provides the foundational emergence model that informs GTC.