Speaker Diarization
Make multi-person recordings usable by separating speech into speaker-labeled segments. Designed for meetings, interviews, panels, and podcasts, diarization improves clarity and reduces time spent manually identifying who said what. An editable timeline supports fast corrections, and the resulting structure improves downstream tasks like dubbing, captioning, and accurate summaries.
Key Features
- Reliable speaker separation: Groups speech by speaker for clear “who said what” transcripts.
- Editable speaker timeline: Merge/split speaker segments for fast correction when needed.
- Built for real conversations: Handles interruptions and rapid back-and-forth more effectively than basic tools.
- Unlocks better dubbing/captions: Improves multi-speaker dubbing and subtitle accuracy by clarifying speaker turns.
Related Products
What you'll create
Teams cleaning up meeting recordings
Turn a messy multi-person call into a labeled transcript so you can see exactly who said what without scrubbing the audio yourself.
Journalists transcribing interviews
Separate your questions from each source's answers automatically, making long interviews far faster to quote, fact-check, and write up.
Podcasters producing show notes
Get a turn-by-turn timeline of hosts and guests, so building chapter markers, quotes, and accurate show notes takes minutes instead of hours.
Researchers analyzing panels and focus groups
Attribute speech to the right participant across overlapping conversation, giving your qualitative analysis clean, per-speaker structure.
How it will work
- 1
Add your multi-speaker recording
Bring a meeting, interview, panel, or podcast file. The tool is built for real conversations with interruptions and rapid back-and-forth.
- 2
Speakers get separated and labeled
Speech is grouped by speaker into a clear "who said what" transcript, with each turn placed on a timeline you can review.
- 3
Correct and export the result
Merge or split segments on the editable timeline to fix any mix-ups, then export a structure that also improves downstream dubbing and captions.
Frequently asked questions
- What audio formats will speaker diarization support?
- We're finalizing the supported list, and the plan is to cover the common meeting, interview, and podcast recording formats. Exact formats will be confirmed on this page at launch.
- How many speakers can it tell apart?
- The tool is designed for real multi-person conversations—meetings, interviews, panels, and podcasts—rather than just two people, and it aims to handle interruptions and rapid back-and-forth.
- Can I fix it when a speaker is labeled wrong?
- Yes—an editable speaker timeline is planned so you can merge or split segments to correct mistakes quickly instead of re-running the whole file.
- Is diarization the same as transcription?
- Not quite. Transcription turns speech into text; diarization figures out who spoke when and labels each turn. Together they produce a clear, speaker-attributed transcript.
- When will Speaker Diarization launch?
- It's an upcoming tool we're building now. We're not setting a launch date yet—check back here or follow us on X for the announcement when it's live.