Speaker Diarization — Know Who Said What
Automatically identify and label different speakers in your audio. Perfect for meetings, interviews, podcasts, and multi-speaker recordings.
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How Speaker Detection Works
Upload
Drop your audio or video file with multiple speakers. Works with meetings, interviews, podcasts, and more.
AI Analysis
Our pyannote.audio model analyzes voice patterns, detecting unique speakers and when they speak.
Labeled Output
Get a transcript with each segment tagged by speaker. Rename speakers to real names with one click.
Speaker Diarization Features
Up to 10 Speakers
Detect and separate up to 10 different voices in a single recording.
90%+ Accuracy
State-of-the-art pyannote.audio model with excellent accuracy for clear recordings.
Timestamped Segments
Every speaker change is timestamped for easy navigation and reference.
Voice Fingerprinting
Unique voice patterns ensure consistent speaker identification throughout.
Rename Speakers
Replace "Speaker 1", "Speaker 2" with actual participant names in one click.
Click to Play
Click any segment to jump to that moment in the audio player.
Perfect For
Team Meetings
Track who said what in team discussions and decisions
Interviews
Separate interviewer and interviewee responses cleanly
Podcasts
Label hosts and guests for show notes and transcripts
Legal Depositions
Document witness testimony with speaker attribution
Focus Groups
Analyze multiple participant responses by speaker
Conference Calls
Identify speakers in remote meetings automatically
Frequently Asked Questions
Try Speaker Diarization Now
Upload your multi-speaker recording and see automatic speaker detection in action.
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