Church Translate, as it runs at the campuses

Live sermon translation into 100+ languages, running entirely on one Mac per campus: audio in, voice detection, Whisper on the GPU, NLLB-200 in its own process, and a built-in web server the congregation reads from on their phones. No audio leaves the building. This is the source only. What used to sit beside it — 14 GB of speech and translation models, 8 GB of voice bundles, 6 GB of natural voices, the Electron caches, and the app data holding the operator PIN and every service transcript — is machine state and downloaded assets, and stays in the NAS backup where it belongs. The vendored node, cloudflared and Windows ffmpeg binaries are out too (533 MB, re-fetched for packaging); the browser-side runtime beside them is kept, so a checkout still serves the congregation page. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-23 15:41:21 -04:00
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+# 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](https://withkaleo.com/) is $24–149/month and
+[OneAccord](https://www.oneaccord.ai/) 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
+
+- **[docs/SETUP.md](docs/SETUP.md)** — installing at a campus
+- **[docs/AUDIO.md](docs/AUDIO.md)** — Dante, Waves SoundGrid, console USB
+- **[docs/COMPANION.md](docs/COMPANION.md)** — the Stream Deck button
+- **[docs/SUNDAY.md](docs/SUNDAY.md)** — print this and tape it to the desk
+- **[docs/PUBLIC-ACCESS.md](docs/PUBLIC-ACCESS.md)** — optional, for people off-site
+
+```bash
+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.