christianandClaude Opus 5 acfca90836 The English switch did nothing, so English could not be turned off
Build 125. Reported from the desk: every language on the listener page can be
switched off except English.

Exactly right, and it was not subtle. renderFeatured() unshifted the SOURCE
language into the list on every render, whatever the operator had chosen:

    if (list.indexOf(app.cfg.sourceLanguage) === -1)
      list.unshift(app.cfg.sourceLanguage);

So English was not merely on, it was always FIRST — the leading button on the
page — on a desk whose saved list was ["spa_Latn","por_Latn","por_PT","spa_ES"]
with English deliberately off and allowAll false. The operator had turned it
off, the config recorded that it was off, and the page put it back anyway.

The reasoning behind it was sound: people do want the English captions for
accessibility rather than translation. But that is a choice for the desk, not
for this function, and the switch to make it is already there in Settings next
to every other language. English is in the catalogue (languages.js:19) and the
operator window reads that same file, so turning it back on is one click.

A control that silently refuses is worse than no control. The operator's list
is now the list.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-10-15 15:17:15 -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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CSS 4.8%
HTML 4%
Shell 1%