> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ospribrain.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Transcription

> How meeting transcripts are generated with speaker diarization.

## How Transcription Works

Ospri Brain uses a two-stage transcription process:

### Stage 1: Real-Time Streaming

During the meeting, the bot streams **live transcript segments** as they're spoken. These appear in real-time and are useful for monitoring but may have lower accuracy.

### Stage 2: Final Transcript

After the meeting ends, the full recording is processed through **Deepgram** (or Recall.ai's built-in transcription) to generate a high-quality final transcript. This replaces the real-time segments with a more accurate version.

## Speaker Diarization

Ospri uses **Perfect Diarization** — each speaker is identified separately using individual audio streams when available (e.g., on Microsoft Teams). This means:

* Each speaker gets a consistent label throughout the transcript
* No confusion between speakers even in fast-paced conversations
* Names are matched to calendar attendees when possible

## Viewing the Transcript

1. Click any meeting in the Recordings tab
2. Go to the **Transcript** tab
3. The transcript is displayed chronologically with:
   * **Speaker name** (bold)
   * **Timestamp** (clickable if video is available)
   * **Spoken text**

<Note>
  **Alex's screenshot note:** Take a screenshot of the Transcript tab on a meeting detail page showing 5-6 transcript entries with different speaker names and timestamps.
</Note>

## Transcript Status

| Status          | Meaning                                                |
| --------------- | ------------------------------------------------------ |
| **Pending**     | Meeting ended but transcript hasn't been generated yet |
| **In Progress** | Transcript is currently being generated                |
| **Done**        | Full transcript is available                           |

## Accuracy Notes

* Final transcripts are generated with **accuracy-prioritized** settings
* Speaker identification uses separate audio streams when the platform supports it
* For platforms without separate streams, AI-based speaker separation is used
* Medical and scientific terminology is generally handled well but may occasionally need manual correction

## Transcript Deduplication

The system automatically prevents duplicate transcript segments. A unique index on `(meeting_id, speaker_name, start_time)` ensures each spoken segment is stored exactly once, even if real-time and final transcription processes overlap.