Speaker Diarization

Know Who Said What

Scribers automatically identifies and labels each speaker in your audio. No manual tagging, no guesswork — just clear, labeled transcripts.

Example Transcript

00:12

Speaker 1: I think we should focus on the Q2 roadmap first before addressing the backlog.

00:18

Speaker 2: Agreed. The marketing team needs the analytics dashboard by March.

00:24

Speaker 1: Let's prioritize that. Can we get a timeline from engineering?

00:30

Speaker 3: I can have estimates ready by Friday. We'll need to scope the API changes first.

How It Works

Step 1

Drop any audio file — meetings, interviews, podcasts, or calls

Step 2

Our AI analyzes voice patterns and labels each speaker automatically

Step 3

Download your transcript with clear speaker labels in any format

Know exactly who said what in team meetings and client calls

Separate interviewer and interviewee for easy reference

Label hosts and guests in multi-speaker episodes

Track individual participants across group discussions

Automatic speaker detection — no setup or training required

Export with speaker labels in TXT, SRT, VTT, DOCX, and JSON

Works with meetings, interviews, podcasts, and any multi-speaker audio

AI summaries with key points and action items per speaker

Process files of any length — background processing for large files