I developed a translation pipeline with Python, FFmpeg, and the HeyGen interface that produced dubbed and captioned versions of the coalition’s educational videos — delivering 54 videos in 77 languages, embedded into LMS modules and public pages for genuinely worldwide access.
54 Videos, 77 Languages
A library of educational videos only reaches the world if the world can understand it. Manually dubbing and captioning 54 videos into dozens of languages is a non-starter. The answer was an automated pipeline — Python orchestration, FFmpeg for media, HeyGen for dubbing — that could produce and package translations at scale.
Citizen of the Universe, in Every Language
The coalition’s ideal rendered across the world’s scripts — the reach the pipeline was built to deliver.
What I Delivered
Python translation pipeline
Built a Python pipeline orchestrating dubbing and captioning end to end.
FFmpeg media processing
Used FFmpeg to process and package the video and audio at scale.
HeyGen dubbing
Integrated the HeyGen interface to generate dubbed language versions.
Embedded in LMS & pages
Delivered the results into LMS modules and public pages for direct access.
Explore the Translations
Real links from the project — see the work for yourself.
Skills & Tools
The stack behind this build — tap any to see related work.
The Impact
A working translation pipeline that turned 54 educational videos into 77-language dubbed and captioned versions — Python, FFmpeg, and HeyGen doing the heavy lifting, and the results embedded across LMS modules and public pages.
Scale Is the Only Way to Global
You cannot hand-translate your way to 77 languages. Building the pipeline — Python, FFmpeg, HeyGen — made worldwide accessibility a repeatable process instead of an impossible task, and put the coalition’s education in front of anyone, in their language.
