About the Translation Technology Course

This project was completed as part of a Translation Technology course, which focused on the tools, workflows, and technical decision-making that support professional localization projects.

Throughout the course, I worked extensively with CAT tools, primarily Trados Studio, while also gaining exposure to tools such as MateCat, AntConc, and other corpus and QA utilities. The course emphasized not only how to use these tools, but why and when they are most effective within a localization pipeline.

Key areas of focus included building and managing translation memories, glossaries, termbases, and style guides, as well as preparing accurate quotes and Statements of Work based on scope, volume, and technical complexity.

We also explored the evolving role of machine translation and AI in the industry—examining when MT can improve efficiency, when human expertise is essential, and how post-editing and QA practices help maintain quality and consistency.

This final project applies those concepts in a real-world scenario, demonstrating how translation technology, linguistic expertise, and project planning come together in a structured localization workflow.

For this project, I localized the mobile game Crayon Shin-chan: Little Helper with the goal of ensuring that players across regions could engage with the game naturally, intuitively, and joyfully in their own language.

The project involved translating all user-facing content from English into Korean, French, and Traditional Chinese, using Trados Studio as the backbone of the technical and linguistic workflow. From early preparation—file validation, segmentation rules, and translation memory setup— to production and final QA, each phase was designed to reduce risk, maintain consistency, and support high-quality multilingual output.

Below is a breakdown of the localization process, supported by examples from each phase, as well as the full Statement of Work and a summary of lessons learned.

Statement of Work

Localization Process Highlights

Pseudo-translation example
Pseudo-translation used to validate segmentation, placeholders, and string expansion.
User-facing string translation
Translation of user-facing strings in Trados using TM matches, QA checks, and concordance search. LQA was conducted for all locales.
DTP Korean asset DTP French asset DTP Traditional Chinese asset
DTP recreation of assets with embedded text across Korean, French, and Traditional Chinese.
Localization glossary
Project glossary ensuring consistent terminology across all languages.
Lessons Learned and Takeaways from this project.