In this case study, we present the process that Localex Team implemented in order to successfully complete one of our Microsoft MT Post-Editing projects. The case study will cover mainly:
The tools, processes and methods used for this project are by no means restricted to a post-editing project, but could be used for any project involving the outsourcing of tasks to remotely-located individuals.
Our client was looking for a reliable partner to localize their IT related contents into various languages in order to expand their customer base and make their products more competitive in foreign markets. They needed a single trusted provider who could take care of their multilingual projects, and manage the post-editing process of machine-translated outputs.
We benefit from a set of post-editing rules prepared by localization industry organizations, which describe in detail the goals of the task and instruct post-editors on how to work on machine-translated output.
All linguists work remotely, accessing post-editing assignments through a cloud-based workflow automation ecosystem.
Machine translated outputs are reviewed by human post-editor teams. Additional quality control is performed by the quality control team at Localex.
.vtt, .srt, .ts, .ttml, .xlf, .oft, .pptx etc.
subtitles for product descriptions and help center,
IT-related technical materials,
English (USA) into Turkish, Chinese (Simplified), Spanish (Spain), French (France), Japanese, German (Germany), Korean, Russian, Italian, Portuguese (Brasil), Chinese (Traditional, Taiwan), Indonesian, Vietnamese, Romanian (Romania), Slovenian, Serbian (Latin), Croatian, Bulgarian, Latvian, Arabic, Polish, Greek, Czech, Hungarian, Hebrew, Malay, Thai, Filipino, Dutch, Swedish, Sinhalese, Lithuanian
We work with both in-house and trusted freelance language professionals. However, for a project this big, we needed to expand our teams to 20+ linguists for some languages and to 100+ linguists in total.
Thanks to our translation technology partner Smartcat’s 250,000-strong marketplace, we were able to quickly find new post-editors and add them to the translation process.
Using these guidelines, our post-editor team learn to make only necessary changes to the MT output by;
We expect from our linguists for;
Linguists are also able to check the status of their progress in order to manage their time more efficiently.
The source files have be to pre-processed by our developer to make them localization friendly.
After the localization process over, the target files have to be post-processed to make them work on the client’s environment again.
Problem: Source files (xlf) are structurally not localization-friendly.
Detailed QA process requirement
Production phase was followed by QA 1, import back, and QA2 steps. Within first QA step, team mainly focused on linguistic checks and the custom placeholders which required custom checklist items. Afterwards the translated output was imported back to their intended locations in the original files.