Speaker Diarization

Know exactly who said what in any audio recording. AI automatically identifies and separates speakers. Works with meetings, interviews, podcasts, and call recordings. Optional speaker enrollment for named identification.

See Features

Integrates with the tools you already use

ShopifyAmazonStripeSlackNotionVercel
95%+

Accuracy

Speaker separation

Unlimited

Speakers

Auto-detected

Real-time

Processing

Live & batch

Named

Enrollment

Optional

A powerful alternative to
Manual AttributionGoogle DiarizationAWS TranscribeAssemblyAI

Diarization Flow

From audio to attribution

Input

Multi-speaker audio

Detect

Identify speakers

Label

Assign identity

Output

Attributed text

Diarization Features

Complete speaker identification

Auto-Detection

Find all speakers

Enrollment

Named speakers

Timestamps

Precise timing

Overlap Handling

Simultaneous speech

Transcription

Combined output

Multi-language

All languages

API Access

Integrate anywhere

Secure

Private processing

Diarization Success

Results from customers

"Meeting transcripts with perfect speaker attribution. No more guessing who said what."

Perfect Attribution

Tech

Admin Lead

"Sales call analysis with speaker metrics. Agent vs customer talk time tracked automatically."

Automatic Metrics

SaaS

Sales Ops

Why Speaker Diarization

Benefits for your audio

Accuracy

  • 95%+ Accuracy

    Reliable

  • Overlap Handling

    Complex audio

  • Named Enrollment

    Known speakers

  • Timestamps

    Precise timing

Use Cases

  • Meetings

    Who said what

  • Call Analytics

    Agent vs customer

  • Interviews

    Q&A separation

  • Podcasts

    Multi-host

Get Started

Diarization in 4 steps

1

Upload Audio

Multi-speaker

2

AI Analyzes

Finds speakers

3

Labels Applied

Speaker 1, 2...

4

Download

Attributed transcript

Diarization Pricing

Pay per minute processed

FAQs

Speaker Diarization

How many speakers can it identify?

Unlimited speakers. AI automatically detects the number of unique speakers and assigns labels to each.

Can I identify known speakers?

Yes, with speaker enrollment. Upload voice samples and the system will identify enrolled speakers by name.

Does it work with overlapping speech?

Yes, AI can handle overlapping speech and separate simultaneous speakers in most cases.

What accuracy can I expect?

95%+ accuracy for speaker separation. Higher with speaker enrollment. Accuracy improves with audio quality.

Ready to Identify Speakers?

Start with a free trial