Word-level transcription
Forced alignment with confidence scores so every beep and cut lands on real boundaries — not guessed silence.
Web platform · podcast & production audio
Upload a file. Get word-level timestamps, automatic profanity detection, and a cleaned track — beep it, or remove it — without opening a DAW.
So the whole pitch was fine until someone said f**k and the room went quiet.
// capabilities
Transcription, alignment, and audio surgery in one queue — built for podcast pipelines, not generic “AI audio” toys.
Forced alignment with confidence scores so every beep and cut lands on real boundaries — not guessed silence.
Flag target language in the transcript, then apply the edit on the waveform with crossfades so you don’t hear a hard cut.
Classic 1 kHz fill over the exact word duration. Useful when you need the airtime preserved for pacing.
Strip awkward pauses and tighten speech cadence while keeping natural rhythm — not a nuclear “remove all silence” pass.
WebSocket updates from queue → processing → complete. No refresh-spam while a long episode cooks.
First runs don’t need a signup. Create an account when you want history, podcasts, and billing.
// the cut
The old way burns an hour of producer time per episode. Autocensor turns the same problem into a job you can queue.
You listen at 1.5×, mark the swear, razor it, drop a beep, check the crossfade, export, re-listen for the pop you just introduced.
Transcribe once. Flag once. Render a cleaned master with the mode you chose — beep or surgical remove — while you move on.
// requirements
// get started
Open /upload, choose options (beep, remove, silence), and send the job.
Transcribe → align → edit. Live status on the job page while workers process.
Grab processed audio plus the timestamped transcript. Account optional for history.
No app download. No credit card gate for a first pass. Upload, censor, download.