# What is speaker diarization? > Speaker diarization is the tech that finds who spoke when in a recording and splits it by voice. How it differs from speaker labels and what goes wrong. Source: https://learn.ynteractive.com/content/glossary/speaker-diarization · Updated 2026-10-19 · Free from Stepthrough (https://learn.ynteractive.com) [Voice agents](https://learn.ynteractive.com/content/glossary#topic-voice-agents) · [AI glossary](https://learn.ynteractive.com/content/glossary) Quick answer Speaker diarization is the part of a transcription tool that listens to a recording and works out who spoke when, splitting the audio into turns by voice. It answers "how many voices, and which one is talking now", and the result is the speaker tags you see on each line. Last updated October 19, 2026 [Take the free module →](https://learn.ynteractive.com/courses/ai-apps-worth-knowing/31)Module 31 of the free [AI Apps Worth Knowing](https://learn.ynteractive.com/courses/ai-apps-worth-knowing) course, about 10 minutes. No account needed. Updated October 19, 2026 · By [Robert Breen](https://learn.ynteractive.com/content/about) ## Why it matters for a small business A transcript with no speakers is hard to use for client work. If an interview says "the fee was a surprise", you need to know whether the client said it or your own staff did, because one is a complaint and the other is a guess. Fixing that by hand means replaying the audio and marking every turn, which is slow work nobody budgets for. Diarization does that marking automatically. It does not know names, though. It hears that two voices differ and calls them Speaker 0 and Speaker 1. Similar voices, crosstalk and a poor microphone can merge two people into one or split one person into two. That is why you check the speakers against what you know before you quote anyone. ## In a real lesson: Speak AI: Turn Customer Interviews into Themes and Quotes In the free [Speak AI lesson](https://learn.ynteractive.com/content/speak-ai-turn-customer-interviews-into-themes-and-quotes), the Harbor Lane Accounting interview is two computer voices reading a made-up script. When the transcript opens, Speak AI has split the call by voice: **Speaker 0** is Dana, the owner, and **Speaker 1** is Mike, the client. Each turn has a play button and a time, such as 00:25. The Insights tab adds that this is **A 1-on-1 conversation**, and the panel has a separate Speakers tab. When you export to Word, **Display speaker names** is on, so the file keeps who said what. Knowing Speaker 1 is the client is what lets AI Chat quote Mike's complaints instead of Dana's questions. [Try this lesson free](https://learn.ynteractive.com/modules/speakai-customer-interview-themes) or [read the step-by-step guide](https://learn.ynteractive.com/content/speak-ai-turn-customer-interviews-into-themes-and-quotes). ## Common confusions ### Speaker diarization vs speaker labels Diarization is the process that splits a recording by voice. [Speaker labels](https://learn.ynteractive.com/content/glossary/speaker-labels) are its output on the page, such as "Speaker 1:" or a name someone added. ### Speaker diarization vs speech-to-text [Speech-to-text](https://learn.ynteractive.com/content/glossary/speech-to-text) writes down the words. Diarization decides whose words they are. Most tools run both on the same upload. ## Tips - Write down which speaker number is which person as soon as you open a transcript. - Use a separate microphone per person on important calls; clearer voices split better. - Listen to a turn or two where people interrupt each other, since that is where splits go wrong. ## Related terms [Speaker labels](https://learn.ynteractive.com/content/glossary/speaker-labels) · [Speech-to-text](https://learn.ynteractive.com/content/glossary/speech-to-text) · [Meeting transcript](https://learn.ynteractive.com/content/glossary/meeting-transcript) · [Word error rate (WER)](https://learn.ynteractive.com/content/glossary/word-error-rate) · [Call summary](https://learn.ynteractive.com/content/glossary/call-summary) ## More Voice agents terms [Text-to-speech](https://learn.ynteractive.com/content/glossary/text-to-speech) · [Virtual receptionist](https://learn.ynteractive.com/content/glossary/virtual-receptionist) · [Voice agent](https://learn.ynteractive.com/content/glossary/voice-agent) · [Voice cloning](https://learn.ynteractive.com/content/glossary/voice-cloning) ## Where you use it: free lessons - [Speak AI: Turn Customer Interviews into Themes and Quotes](https://learn.ynteractive.com/content/speak-ai-turn-customer-interviews-into-themes-and-quotes) (Speak AI, 10 min) - [Summarize a Meeting Transcript with ChatGPT](https://learn.ynteractive.com/content/chatgpt-summarize-meeting-transcript) (ChatGPT, 9 min) ## AI tools that use it - [Speak AI](https://learn.ynteractive.com/content/ai-tools/meetings-notes#tool-speak-ai) [More terms by tool](https://learn.ynteractive.com/content/glossary/ai-tool-terms) ## Frequently asked questions **Does diarization know people's names?** No. It tells voices apart and numbers them. Names come from you, from a meeting tool that knows who joined, or from a later step. **Why does my transcript show one person as two speakers?** A change of microphone, background noise or a long pause can make one voice sound like two. Check those spots against the audio. **Is speaker diarization the same as voice recognition?** Not quite. Diarization only separates voices within one recording. Voice recognition tries to match a voice to a known person. [All AI glossary terms, A to Z](https://learn.ynteractive.com/content/glossary) · [Free prompt templates](https://learn.ynteractive.com/content/prompts)