How 360 AI Institute Boosted Airline Translation Accuracy from 70% to 96%

Problem and Core Value

Airline maintenance, fault diagnosis, and related documents contain massive specialized terminology with strict "zero‑tolerance" accuracy requirements; any translation error can cause maintenance mistakes, regulatory penalties, or safety hazards. The industry also lacks standardized translation corpora, creating a major obstacle for model training.

High‑Quality Corpus Construction

A parallel corpus and a dedicated terminology database were built to cover maintenance, operations, and training scenarios across different aircraft models and workflow stages. The raw data underwent multiple rounds of deep cleaning: redundant, erroneous, and non‑standard entries were removed; each iteration was manually verified and cross‑checked, producing several refined versions that together form a high‑accuracy, domain‑specific dataset.

Model Optimization

Three techniques were combined:

Retrieval‑Augmented Generation (RAG) multi‑path augmentation : tightly binds the specialized corpus to the model, enabling fast retrieval and precise use of domain knowledge.

Supervised Fine‑Tuning (SFT) : trains the model on the cleaned corpus so it internalizes airline‑specific language patterns and terminology.

Reinforcement Learning (RL) : incorporates feedback on critical airline terms, continuously refining translation output.

Rapid Deployment

Leveraging the maintenance knowledge base and a new technical architecture, the end‑to‑end pipeline—from project kickoff to production deployment—was completed in one month, demonstrating a fast rollout capability.

Evaluation Results

Chinese‑to‑English translation accuracy increased from approximately 70 % to 96 %, eliminating prior compliance and safety risks. English‑to‑Chinese performance showed a comparable improvement (see image).

Outlook

Future work will continue to iterate on the translation system toward higher precision, efficiency, and intelligence, further embedding the technology in airline operations.