Developer Log Made by Rehan Bharwani Jun 02, 2026
Manually aligning voiceovers and making micro-cuts in Final Cut Pro is arguably one of the most tedious, mind-numbing parts of modern video production. When you are producing high volumes of content, timeline synchronization eats up hours of your day. I built Revo Narrator to automate this entirely using Python and the Google AI Text-to-Speech (TTS) engine.
The core script works by parsing a raw text document (such as a video script) and chunking it logically by sentences or paragraphs. It then fires these chunks asynchronously to the Google AI TTS API, generating perfect, studio-quality audio `.wav` files. However, just generating audio isn't enough—you still have to edit it.
This is where Revo Narrator becomes incredibly powerful. Using Python, the system calculates the exact millisecond duration of every generated audio file. It then programmatically constructs an `.fcpxml` (Final Cut Pro XML) document. This XML file maps out a complete video timeline, placing every audio segment sequentially, inserting precise gaps for pacing, and even laying down placeholder b-roll video clips perfectly synchronized to the audio track.
By the time the script finishes executing in the terminal, you simply double-click the generated `.fcpxml` file. Final Cut Pro opens instantly with the entire video already assembled on the timeline. What used to take 3 hours of manual cutting, dragging, and aligning is now accomplished in 12 seconds via Python.
Tech Stack: Python, Google Cloud AI API, XML Generation, Final Cut Pro.