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Speaker labels in transcription, explained
A transcript without speaker labels is a wall of text where you cannot tell who said what. Speaker labels fix that, turning the raw words into a readable conversation. Here is what they are, how the software figures out who is talking, and the easiest way to get a speaker-labeled transcript.
What is a speaker label?
A speaker label is the tag that marks who said each line, like Speaker 1, Speaker 2, or a person's name. Compare these two transcripts of the same exchange:
so are we agreed on Friday yes Friday works can you send the deck I will send it tonight
...versus the same audio with speaker labels:
Maria: So are we agreed on Friday?
James: Yes, Friday works. Can you send the deck?
Maria: I will send it tonight.
Same words, completely different usefulness. That is what speaker labels buy you.
How speaker identification works (diarization)
The technical name is speaker diarization. The software analyzes the audio, detects how many distinct voices are present, and groups each segment by who spoke, producing the generic Speaker 1 / Speaker 2 tags. Those tags stay as Speaker 1, Speaker 2, and so on in the transcript itself — diarization identifies voices, not names. It is a separate step from transcription: transcription turns sound into words, diarization decides who owns each stretch of words.
How to get a transcript with speaker labels
Most enterprise speech-to-text services support diarization, but they are built for developers. For a normal conversation, the simplest path is an app that does it automatically. With Attesta on iPhone you just record:
- Tap record (an audible tone tells the room it has started).
- Have your conversation, then tap stop.
- Get a transcript that is already split by speaker — Speaker 1, Speaker 2, and so on — plus a summary, with no setup.
- Tell Attesta who's who with Refine (for example, "Speaker 1 is Yazan") and the real name carries through to the summary, action items, and people list — even though the transcript itself keeps the Speaker N tags.
Can you rename Speaker 1 and Speaker 2?
Not in the transcript itself. The labels come straight from diarization — a voice, not a name — so the transcript always reads Speaker 1, Speaker 2, and so on. What you can do is use Refine to tell Attesta who's who in plain language. Say "Speaker 1 is Yazan" and that name carries through automatically to the summary, the action items, and the people list, so the parts you actually read afterward are attributed to real people even though the transcript's own labels stay generic.
Does it work with more than two speakers?
Diarization is not limited to a two-person back-and-forth. It separates however many distinct voices are actually in the recording, so a three-person interview, a small panel, or a study group comes back labeled the same way — Speaker 1, Speaker 2, Speaker 3, and so on, in the order each voice first speaks.
Speaker 1: So the review turned up three open risks in the draft.
Speaker 2: Can you walk through the second one?
Speaker 3: Sure — it's the vendor dependency I flagged last week.
Speaker 1: Right, let's put that on Friday's agenda.
Accuracy depends more on the audio than the headcount. Two people a few feet apart, taking clear turns, is the easy case. Five people around one phone, with two of them talking over each other, is the hard case — the same things that help with two speakers (clean audio, distinct voices, no talking over each other) matter even more as the group grows.
Tips for accurate speaker labels
- Clean audio matters most. Background noise and distance blur the line between voices.
- Avoid talking over each other. Overlapping speech is the hardest case for diarization.
- Distinct voices help. Two similar-sounding speakers are harder to separate than two different ones.
- Name people early. When someone says a name out loud, it is easier to map labels to real people.
Get a speaker-labeled transcript automatically, plus a summary and action items, from a single tap.
Download on theApp StoreFrequently asked questions
What is a speaker label?
The tag that marks who said each line in a transcript, like Speaker 1, Speaker 2, or a name. It turns a wall of text into a readable back-and-forth.
How do you identify speakers in transcription?
Software uses speaker diarization to tell voices apart and group each segment by who spoke. The labels stay generic — Speaker 1, Speaker 2, and so on — since diarization identifies voices, not names. Clear audio and distinct voices make it far more accurate.
What is the proper format for a speaker label?
Name or tag, then a colon, then the words, with a new line each time the speaker changes (for example, "Maria: Let's ship on Friday."). Timestamps at each turn are common for interviews and meetings.
How do I get a transcript with speaker labels?
Use a tool that supports diarization. Attesta does it automatically on iPhone: record the conversation and you get a speaker-labeled transcript plus a summary, with no setup. Tell it who's who afterward with Refine, and the real name shows up in the summary and action items.
Can I rename Speaker 1 and Speaker 2 to real names?
Not in the transcript itself — the labels stay as Speaker 1, Speaker 2, and so on. Use Refine to tell Attesta who's who (for example, "Speaker 1 is Yazan") and the real name carries through automatically to the summary, action items, and people list.
Does speaker diarization work with more than two speakers?
Yes — it separates however many distinct voices are actually in the recording, not just two. A panel, a three-person interview, or a study group all come back labeled Speaker 1, Speaker 2, Speaker 3, and so on. Audio quality matters more as the group grows: distance, background noise, and people talking over each other get harder to untangle the bigger the group gets.