Church Translate

Live sermon translation into 100+ languages. One Mac app per campus. No servers, no deployment, no subscription.

Congregants point a phone camera at a QR code, tap their language once, and read along — or let their phone read it aloud in their ear. No app, no account.

Built because Kaleo is $24–149/month and OneAccord starts at $150/month for five hours, and both are wrappers around cloud speech and translation APIs that an M-series Mac runs locally for nothing.

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How it works

Everything is inside the one app. Install it on the Mac at a campus, point it at the pastor's microphone, and it serves the congregation page itself.

   ┌──────────────── one Mac, one campus ─────────────────┐
   │                                                       │
   │  Dante ─┐                                             │
   │  Waves ─┼─► audio in ──► voice detection              │
   │  M32 ───┘                     │                       │
   │                               ▼                       │
   │                     Whisper  (Mac GPU)                │
   │                               │                       │
   │                     NLLB-200  (separate process)      │
   │                               │                       │
   │                     built-in web server ──────────────┼──► phones on
   │                                                       │    the WiFi
   └───────────────────────────────────────────────────────┘

No audio ever leaves the Mac, and nothing leaves the building unless you choose to publish it. Only finished sentences cross the network, so a full auditorium costs almost nothing to serve.

Two details that are not preference but necessity: translation runs in its own plain-Node child process, because Chromium's allocator refuses the model's gigabyte-sized weight blocks and kills the process; and speech recognition runs on the GPU while translation runs on the CPU, because neither fits in the other's runtime.

What it costs

Speech recognition	Whisper large-v3-turbo, on the Mac's GPU — $0
Translation, 100+ languages	NLLB-200, on the Mac's CPU — $0
Spoken audio	The listener's own phone — $0, at any scale
Serving the page	The app itself — $0
Dante input	Dante Virtual Soundcard, ~$50 once per campus — or free via Waves or console USB

Performance

Measured on an M2 Max, from the end of a spoken sentence to captions on a phone. Partial text appears well before that, so it feels quicker than the numbers.

Live preview	updates every 500–800 ms while the sentence is still being spoken
Finished sentence	~1.6 s behind the speaker
Speech recognition	4.9× real time (accurate model)
Translation	~390 ms per language, flat over 240 consecutive runs
Memory	plateaus at 10–11 GB; no drift across a long service

Two speech models run at once: a fast one drives the live preview, an accurate one produces the line the congregation keeps. They run on separate tracks, so the preview costs the finished caption almost nothing.

Getting started

• docs/SETUP.md — installing at a campus
• docs/AUDIO.md — Dante, Waves SoundGrid, console USB
• docs/COMPANION.md — the Stream Deck button
• docs/SUNDAY.md — print this and tape it to the desk
• docs/PUBLIC-ACCESS.md — optional, for people off-site

cd app && npm install && npm start     # run from source
cd app && npm run dist                 # build the .app

Things worth knowing

• Only languages people are actually listening to get translated. Nobody on Icelandic means no CPU spent on Icelandic. Pin a language on the operator page to have it ready before the first person arrives.
• Corrections beat retraining. Operator page → Corrections → have a cook => Habakkuk. Whole-word, case-insensitive, instant.
• A late arrival sees the last 40 lines, so walking in halfway still makes sense.
• Transcripts are written per service, original and every translation, under ~/Library/Application Support/Church Translate/data/transcripts/.
• Each campus is independent. Nothing is shared, nothing syncs, and one campus being down has no effect on another.