Transcria ... Yet another open-source transcription project — except it got a little out of hand
Fair warning: the world does not need another Whisper wrapper, and that isn't quite what I set out to build. It started for a handful of real users who needed meeting minutes and were tired of paying per minute to ship confidential recordings to a cloud they didn't control. It ended up running inside two companies, which was honestly all I ever wanted from it.
The problem is that I'd already started. You know how that goes.
The summary came from a local LLM, so I figured the LLM might as well correct the SRT using a validated lexicon and the meeting context. Then I wanted better speaker attribution, so I wired in pyannote, later Sortformer, benchmarked a few STT backends against each other, and built a per-VRAM-tier model catalog because "which model fits my GPU" is a question I got tired of answering by hand. Somewhere along the way it grew a GPU job queue, calendar scheduling, a resumable pipeline, multi-user roles, an audit trail, and a full-screen transcript editor. I keep promising people the next feature is the last one. They've stopped believing me.
What I think actually sets it apart isn't the models — we all pull from the same shelf. It's the unglamorous parts. A human-in-the-loop step where you validate speakers from audio excerpts and a domain lexicon before the final pass. Deliverables you can chat with, then fix a term once and have it corrected coherently across the SRT, the summary and the Word minutes. And the boring production plumbing you only miss once real people use the thing every week: "waiting for VRAM" as an actual state instead of a crash, a pipeline that resumes instead of redoing four hours of audio, and a split mode where a CPU web front talks to a separate GPU node.
I tried to keep the code honest — tests, CI, a coverage gate — mostly so future me doesn't resent present me.
Honest caveats before anyone gets ideas: the UI is French-first for now (strings are centralized, so it's a translation job, not a rewrite), reference quality leans on gated models, and you need an NVIDIA GPU. Apache-2.0.
I'd genuinely value a specialist eye on the diarization and STT-arbitration choices — this is one of the few rooms where people actually know where the bodies are buried in this domain. Repo and a few screenshots below.
