Paste a labeled transcript
Names on the lines, as in a Zoom VTT with speakers.
Paste a transcript that already has speaker names and see each name’s share of the words. If there are no names, the page does not guess.
Runs in this browser. The paste never leaves this device.
This is not a score. It is a word count per name already written in the file. Facilitation metrics stay with you. A fiduciary or chair may want the split. A raw M4A cannot provide it here.
The page stops. It will not invent Speaker 1. Diarization is a Mac job. Clean a VTT first only if names are already on the cues.
Timestamps in a VTT are for a player. Cue duration is not speaking time: silence and overlap sit on the clock too. Without clocks the page would have to invent them. Words on labeled lines are the honest count.
Vemoir separates speakers on device from the recording, then you can rename them. This page only reads labels that already exist.
This page never infers speakers. No labels means an honest stop, not a fake Speaker 1.
Counts follow the text you paste. Dialect is not restored.
Names on the lines, as in a Zoom VTT with speakers.
Each name gets a share of the words.
The page will not guess. Use Vemoir for Mac on the recording.
No. Paste text that already has names.
No. There is no speech model on this page.
Counts use the labeled lines. Unlabeled lines are ignored rather than assigned.
The page does not judge. It reports the split.
Yes, if the VTT already contains names. Cue clocks are ignored. Clean timestamps first if you want readable text as well.
No.
It counts whatever text you paste. It does not restore dialect.
Vemoir for Mac, for speaker separation on the machine.
Vemoir for Mac separates speakers on the machine. This page only reads labels you already have.