Waters ChurchandClaude Opus 5 817fb743de Show the domain, not the LAN address, once one is set
Build 122. The operator page honoured Public address and the main app window
did not, so the two disagreed about the one fact they both exist to display:
translate.watersmedia.org was configured and working through nginx, while the
window, the QR code, the poster and Copy address all still handed out
http://10.1.7.39:3100.

engine.js had no mention of publicUrl at all. It now reads it from the server
config it was already fetching, and prefers it everywhere the congregation is
pointed.

The operator link deliberately does not follow. /operator returns 404 to
anything carrying X-Forwarded-For, so over a proxy the domain is exactly where
that page cannot be reached; it stays on the LAN address, which is the whole
point of being able to run the desk from a phone.

The QR warnings are suppressed when a public address is set. They talk about
Wi-Fi being down and leases moving, which are facts about an address nobody is
being given any more; the panel now names the public address and reminds the
desk that this Mac still has to be reachable from the proxy.

The share panel also re-renders when the server config arrives. It is fetched
asynchronously and lost a race at startup, so the first paint had no publicUrl
to read even once this was wired up.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-10-15 13:40:48 -04:00

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.


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

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.
S
Description
Live sermon translation into 100+ languages. One Mac app per campus — captures audio, transcribes, translates, speaks, and serves the congregation page itself. No servers, no subscription.
Readme
6 MiB
2026-10-15 16:05:50 -04:00
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JavaScript 90.2%
CSS 4.8%
HTML 4%
Shell 1%