📘 Translation OS — Language-Agnostic Core

A structure-first translation & QA operating system.
Version 1.0 · Designed by Hideyuki Okabe

⭐ If you find Translation OS useful, please consider giving the repository a star!

Translation OS defines a translation pipeline specification, not a model or service.

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🔥 What is Translation OS?

Translation OS is a reproducible, structure-driven translation operating system that eliminates semantic drift and ensures deterministic, evidence-based translation quality across languages, models, and reviewers.

Unlike conventional translation or LLM prompting, Translation OS is:

• model-agnostic

• language-agnostic

• structure-first

• evidence-based

• reproducible

It treats translation not as sentence rewriting but as:

Meaning → Structure → Evaluation → Refinement

This is the foundation of a deterministic translation workflow.

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🧠 Core Concepts

Semantic Nucleus Extraction

Meaning is extracted as minimal, language-agnostic units.

Cross-Lingual Structural Mapping

Structures are normalized before generation.

ΔS (Structural Entropy)

Measures structural drift and instability.

META Evaluation (YES/NO Gate)

Ensures strict structural alignment.

Human-in-the-loop Cultural Layer

Cultural judgment is intentionally not automated.

For the full theoretical foundation:
👉 docs/translation_os_core.md

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🏗 Architecture Overview

flowchart TD
  IN["Input<br/>Source text / Constraints / Domain profile"]

  P1["Phase 1: Semantic Nucleus<br/>Semantic core extraction"]
  P2["Phase 2: Structural Mapping<br/>Structural template mapping"]
  P3["Phase 3: Draft Synthesis<br/>Draft generation"]
  P4["Phase 4: META Evaluation<br/>Binary YES–NO gate"]
  P5["Phase 5: ΔS Refinement<br/>Structural entropy optimization"]
  P6["Phase 6: Human-in-the-loop<br/>Final human decision"]

  OUT["Output<br/>Final translation<br/>Evidence log + ΔS profile"]

  IN --> P1 --> P2 --> P3 --> P4
  P4 -->|YES| P5 --> P6 --> OUT
  P4 -->|NO| P2

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A deterministic, structure-first translation pipeline with explicit evaluation gates and human oversight.

Architectural Layers (Conceptual)

The pipeline shown above is implemented on top of the following conceptual layers:

• Philosophical Core — design principles and epistemic constraints
• Structural Engine — language-agnostic structural normalization
• Six-Phase Translation Pipeline — deterministic execution flow
• Unified Evaluation Matrix — explicit QA and decision logic
• Counter-Evidence System — failure detection and rejection paths
• Recursive Refinement Engine (ΔS) — structural stability control
• QA Testing Framework — reproducibility and validation layer

More details:
👉 docs/architecture.md
👉 docs/pipeline.md
👉 docs/overview.md

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🎯 Why Translation OS Matters

Translation OS addresses critical failure points in MT and LLM-based translation workflows:

• Eliminates semantic drift across models and reviewers
• Enables reproducible, audit-ready QA
• Makes evaluation logic explicit and inspectable
• Supports human-in-the-loop safety by design
• Decouples translation quality from model behavior

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🌐 API Endpoints (v1.0)

Translation OS exposes five minimal REST endpoints:

POST /v1/semantic-core
POST /v1/structure-remap
POST /v1/synthesize
POST /v1/evaluate
POST /v1/refine

Full API specification and examples:
👉 api/endpoints.md
👉 api/openapi.yml

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📂 Repository Structure

translation-os/
├── README.md
├── LICENSE
├── api/
│ ├── endpoints.md
│ ├── openapi.yml
│ └── examples/
├── docs/
│ ├── overview.md
│ ├── architecture.md
│ ├── pipeline.md
│ └── translation_os_core.md
└── examples/

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📜 License

MIT License (recommended for open-source + enterprise adoption)

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📩 Contact

For enterprise use, PoC inquiries, or collaboration:
LinkedIn → Hideyuki Okabe

📄 Resume / Professional Profile

For a detailed overview of my work in AI-translation systems, multimodal evaluation,
and OS-level framework design, you can view my full professional resume here:

👉 https://docs.google.com/document/d/1lhnRh5fFQlPYTGh4yqXJwJAp5ubmelRpRgL7FoPIcfw/edit?usp=sharing

This document includes:

• Technical background in Translation OS, Unified Cognitive OS, SYNAPSE, and evaluation frameworks
• Experience with LLM-based QA, deterministic pipelines, and cross-lingual system design
• Industry projects (Gengo, TransPerfect, Hansem Global, etc.)
• Research direction and system architecture philosophy