Diarization
Identify and label the speakers in multi-speaker Arabic audio, then get each speaker segment aligned with transcribed text and timestamps — who said what in meetings, interviews, podcasts and conversations.
Endpoint
Authenticate with your API key in the x-api-key header. See Authentication.
| Header | Value |
|---|---|
x-api-key | YOUR_MUNSIT_API_KEY |
Request
Send the body as multipart/form-data. How it works: you upload a multi-speaker file, Munsit identifies speaker turns and assigns speaker labels, and you receive transcription, diarization segments, and merged speaker-labeled text with timing.
| Field | Type | Required | Description |
|---|---|---|---|
file | file | Yes | Audio file in a supported format — see what you can send. |
model | string | No | ASR model to use: munsit (default) or munsit-en-ar (mixed Arabic-English with code-switching). |
Example request
Works like Transcribe, with speaker labels added to the response.
Response fields
Three views of the same audio arrive under data: the raw transcript, the speaker segments, and the two merged together.
| Field | Type | Description |
|---|---|---|
transcription | object | Transcript and word-level timestamps. |
diarization | object | Speaker segments with start/end labels. |
merged | array of objects (start, end, speaker, text) | Combined diarization + transcript. |
duration | number | Total duration in seconds. |
transcriptionId | string (UUID) | Transcription identifier. Use it as the path parameter for diarization sentiment analysis. |
originalTranscript | string | Raw verbatim transcript. |
attributes | object | Internal metadata blob persisted with the transcription. Prefer the named fields — treat this as unstable. |
audioUrl | string | Stored copy of the uploaded audio. See Audio retention. |
stats | object (fileName, fileSize, mimeType, creditsConsumed) | Upload metadata and the credits billed for this request. |
merged. Each entry is one speaker turn — speaker, its text, and start/end timing — ready to render as a conversation.
Go further
What to run on a diarized conversation next.
Working with an AI assistant? Every page is available as Markdown: add .md to the URL, or send an Accept: text/markdown header. For the whole documentation in one request, point it at llms-full.txt; the page index is llms.txt. Or use Copy Page, top right.