What is Speaker Diarization?
Speaker diarization is the process of identifying and separating different speakers in an audio recording or live conversation. It answers the question "who spoke when" without necessarily identifying who the speakers are by name.
How Speaker Diarization works
Diarization algorithms analyze voice characteristics (pitch, timbre, speaking rate) to create a voice profile for each unique speaker and assign each segment of speech to the correct speaker. In real time applications, the system builds speaker profiles on the fly as the conversation progresses. Accuracy is typically measured by Diarization Error Rate (DER), with production systems targeting under 10%.
Why Speaker Diarization matters for enterprise
Speaker diarization is critical for call analytics, compliance recording, meeting transcription, and quality assurance. In contact center voice AI, it separates the AI agent's speech from the caller's speech for accurate conversation logging and analysis.
How ARCA handles Speaker Diarization
ARCA uses speaker diarization to maintain separate transcripts for the AI and the caller, enabling accurate call analytics and compliance logging.
See how ARCA uses speaker diarization in practice.
Book a demo