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LLM-Native Craft · 1 min read

Speaker diarization and labeling across multi-speaker recordings

Who said what, when — diarization is deceptively hard in real, multi-speaker, multilingual audio. How we identify, segment and label speakers consistently across recordings.

By Cognegica Quality & Standards

QA & annotation-standards team

Illustration representing speaker diarization

Diarization — attributing each segment of audio to the right speaker — sounds simple until you meet real recordings: people interrupt, talk over each other, switch languages mid-sentence and sit at different distances from the mic. Getting it right is a discipline, not a button.

Segment first, then attribute

We timestamp and segment audio at a defined granularity before attributing speakers, so segment boundaries are consistent across a delivery.

Identify speakers consistently

Speaker identification and diarization are applied across multi-speaker recordings with a consistent labeling scheme, so the same speaker is tracked the same way throughout.

Pair diarization with event tags

Overlapping speech is marked with the [overlapping speech] tag and attributed where possible — diarization and non-speech event annotation work together rather than in isolation.

Native linguists, every language

Diarization across scripts and dialects needs native-linguist judgement. It feeds directly into downstream training and evaluation where speaker structure matters.

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About the author

Cognegica Quality & Standards

QA & annotation-standards team

Cognegica Quality & Standards is the internal team that defines and enforces our annotation guidelines, multi-layer QA, native-linguist review and inter-annotator agreement reporting. This is an editable team identity — a named reviewer with a public profile can be assigned to it later in the admin.

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