AI Speaker Diarization

Know exactly who said what in every recording

Mediata automatically detects and labels each speaker in your audio and video files. No manual tagging needed — just upload your recording and get a clear, speaker-attributed transcript in minutes.

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How speaker diarization works

1

Upload your recording

Drag and drop any audio or video file, or paste a link. Mediata accepts recordings with any number of participants.

2

AI identifies each speaker

Our model analyzes voice patterns, pitch, and timing to separate speakers and assign consistent labels throughout the transcript.

3

Review and refine

See color-coded speaker segments, rename speakers to real names, and export a clean transcript with full attribution.

See it in action

Panel Discussion: Technology Trends 2026

Diarized•47:32•4 speakers
Transcript
Who talked about the cost of AI adoption?

Speaker attribution analysis:

  • James Liu raised the cost-of-adoption concern at 01:14, noting the infrastructure gap for small companies.
  • David Park mentioned privacy benefits of on-device AI but did not address cost directly.
  • Sarah Chen acknowledged James's point and redirected the conversation to open-source accessibility.
Based on 6 transcript segments
Ask about any speaker or topic...

Diarization that actually works

Multi-speaker detection

Accurately separates two, five, or even ten speakers in a single recording. No need to specify the number upfront — the model figures it out.

Contextual AI chat

Ask questions about what specific speakers said. The AI uses speaker labels to give you precise, attributed answers from the transcript.

Searchable transcripts

Find any moment by speaker name, keyword, or topic. Filter by speaker to see only their contributions across the entire recording.

Works with any recording format

Upload files from any device or platform — Mediata handles the rest.

Video files

MP4MKVMOVAVIWebM

Audio files

MP3WAVFLACOGGM4AAAC

Links & streams

YouTubeGoogle DriveDropboxDirect URL

Built for real conversations

Meetings & calls

Capture every voice in team meetings, client calls, and standups. Know who committed to what without rewatching the entire recording.

Interviews & podcasts

Separate host and guest voices cleanly. Perfect for journalists, researchers, and podcast producers who need accurate attribution.

Lectures & panels

Track multiple speakers in conference talks, academic lectures, and panel discussions with clear labeling from start to finish.

Legal & compliance

Produce speaker-attributed records for depositions, hearings, and compliance reviews where knowing who said what is critical.

Your recordings stay private

Speaker diarization processes your files securely. We never use your data to train models, and you can delete your recordings at any time.

  • Recordings deleted on request — no retention
  • Encrypted storage and transfer
  • Your data is never used for model training

Frequently asked questions

How accurate is the speaker diarization?
Mediata's diarization model achieves high accuracy on most recordings with clear audio. Accuracy depends on audio quality, speaker overlap, and background noise. For best results, use recordings where speakers take turns and microphone quality is reasonable.
How many speakers can it detect?
There is no hard limit. The model automatically detects the number of speakers in your recording. It works well with 2 to 10+ speakers, though accuracy is highest when speakers have distinct voices and minimal overlap.
Can I rename the detected speakers?
Yes. After diarization, each speaker is assigned a generic label like 'Speaker 1'. You can rename them to real names directly in the transcript view, and the labels update throughout the entire recording.
What do the color labels mean?
Each detected speaker gets a unique color in the transcript. This makes it easy to scan long recordings visually and quickly identify who is speaking at any point. Colors are assigned automatically and remain consistent.
Does diarization work together with transcription?
Absolutely. Diarization and transcription happen in a single pass. You get a full text transcript with speaker labels attached to every segment — no extra steps required.
What if two speakers talk at the same time?
The model handles moderate overlap reasonably well. In cases of heavy crosstalk, it will assign the segment to the dominant speaker. Very noisy or heavily overlapping sections may have reduced accuracy.
Can I export the speaker-labeled transcript?
Yes. You can copy the full transcript with speaker labels, or use the AI chat to extract specific speaker contributions. The transcript preserves speaker names and timestamps throughout.

Related features

Meeting MinutesInterview TranscriptionVideo TranscriptionPodcast Transcription

Stop guessing who said what

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