> ## Documentation Index
> Fetch the complete documentation index at: https://docs.screenpipe.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Local meeting transcription for Zoom, Meet, and Teams
> Automatically transcribe Zoom, Meet, and Teams meetings locally with Screenpipe using Whisper speech-to-text and speaker diarization — no bot, no cloud.
Screenpipe automatically transcribes all audio from your meetings, calls, and conversations. Local Whisper is the default, and you can also connect an OpenAI-compatible transcription server.
For the full botless meeting workflow - live transcript, speaker cleanup, calendar enrichment, summaries, copy transcript, and APIs - see [meeting intelligence](/meeting-intelligence).
## Languages
Cloud transcription is multilingual. Pick one language in **settings → recording → transcription** to force it, or leave the selection empty (or pick several) for automatic detection — non-English audio is detected and transcribed in its own language, not forced to English.
## Setup
Audio recording is enabled by default in the desktop app. Configure audio devices and transcription engine in **Settings**.
* **Audio devices**: select which microphones and system audio to capture
* **Transcription engine**: choose local Whisper, Deepgram, or an OpenAI-compatible endpoint
## Use a local OpenAI-compatible server
Screenpipe can send uncompressed WAV audio to any server that implements
`POST /v1/audio/transcriptions`. This keeps Screenpipe's capture and search
workflow while letting a separate local runtime own transcription.
[Soniqo speech-swift](https://github.com/soniqo/speech-swift) provides the
endpoint on Apple Silicon. Install and start it on macOS with:
```bash theme={"system"}
brew install speech
speech-server --port 8080
```
On Linux or Windows, use a
[Soniqo Speech Core](https://github.com/soniqo/speech-core) package that includes
the same transcription endpoint. Download the model bundle, then start the
server:
```bash theme={"system"}
# Linux
speech download-models
speech serve
```
```powershell theme={"system"}
# Windows PowerShell, from the extracted package's bin directory
.\speech_download_models.ps1
.\speech-server.exe
```
In **settings → recording → transcription**, choose **OpenAI Compatible** and
set:
* **Endpoint**: `http://127.0.0.1:8080`
* **Model**: `whisper-1`
* **Send raw WAV audio**: enabled
* **API key**: leave empty for a loopback-only server, or enter the server's bearer token
Run **connection test** before restarting capture. The server does not need to
list models; Screenpipe accepts a manually entered model name.
## Search transcriptions
```bash theme={"system"}
# find discussions about a topic
curl "http://localhost:3030/search?q=budget+review&content_type=audio&limit=10"
# get today's meetings
curl "http://localhost:3030/search?content_type=audio&start_time=2026-02-11T00:00:00Z"
# filter by speaker
curl "http://localhost:3030/search?content_type=audio&speaker_ids=1,2"
curl "http://localhost:3030/search?content_type=audio&speaker_name=John"
```
## Speaker identification
Screenpipe automatically identifies different speakers. Manage them via API:
### Improve speaker identification with calendar
Connect your **Google Calendar** to significantly improve speaker identification accuracy. Screenpipe uses your calendar's attendee list to automatically name speakers during meetings — if a meeting has exactly 2 attendees, the other speaker is auto-identified without manual labeling.
To enable this:
1. Go to **settings → connections → Google Calendar**
2. Authorize Screenpipe to access your calendar
3. During future meetings, attendee names from your calendar will automatically label speakers
This works best for 1:1 meetings and structured calls. For larger meetings (3+ attendees), calendar context is tagged to your notes for later reference.
```bash theme={"system"}
# get unnamed speakers for labeling
curl "http://localhost:3030/speakers/unnamed?limit=10"
# update a speaker's name
curl -X POST http://localhost:3030/speakers/update \
-H "Content-Type: application/json" \
-d '{"id": 1, "name": "John Smith"}'
# search speakers by name
curl "http://localhost:3030/speakers/search?name=john"
# merge duplicate speakers
curl -X POST http://localhost:3030/speakers/merge \
-H "Content-Type: application/json" \
-d '{"speaker_to_keep_id": 1, "speaker_to_merge_id": 2}'
# find similar speakers
curl "http://localhost:3030/speakers/similar?speaker_id=1"
```
## Tips
* Use a good microphone
* Reduce background noise
* `whisper-large-v3-turbo` is faster with a small accuracy tradeoff; `whisper-large-v3` is the most accurate
* Set language to English in settings if you only speak English (faster)
## Long meetings and batch sizing
Screenpipe splits long recordings into batches using limits appropriate to each transcription engine.
For **OpenAI-compatible** servers, open **Settings > Audio & meetings** and set **Max batch duration (seconds)** beneath the endpoint configuration. This controls both background batches and meeting retranscription. Leave it blank or set it to `0` to use automatic sizing. Other engines keep their engine-specific limits.
Lower the duration if your server or gateway times out. You can increase it for a faster server, but upload size is only one constraint: the server also needs time to transcribe the audio. Screenpipe allows more request time for longer audio; your gateway may enforce a shorter timeout of its own.
## Privacy
* Local Whisper and loopback OpenAI-compatible endpoints keep transcription on your device
* Audio files stored in `~/.screenpipe/data/`
* Audio is sent off-device only when you select Deepgram or another remote endpoint
* Disable audio recording in app settings
Questions? [join our Discord](https://discord.gg/screenpipe).
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