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local-teleprompter

(★ 9)

AI powered teleprompter running entirely locally on your machine.

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ZIP 다운로드

- - __init__.py
  - agent.py
  - local_stt.py
- - conftest.py
  - test_agent.py
- .dockerignore
- .env.example
- .gitignore
- AGENTS.md
- CLAUDE.md
- Dockerfile
- GEMINI.md
- livekit.toml
- pyproject.toml
- README.md
- uv.lock
- script.png
- teleprompter.png
- - favicon.ico
  - layout.tsx
  - opengraph-image.tsx
  - page.tsx
- - CommitMono-400-Italic.otf
  - CommitMono-400-Regular.otf
  - CommitMono-700-Italic.otf
  - CommitMono-700-Regular.otf
- - use-scripts.ts
  - useAgentErrors.tsx
  - useDebug.ts
- - scripts-db.ts
  - utils.ts
- - commit-mono-400-regular.woff
  - everett-light.woff
  - lk-logo-dark.svg
  - lk-logo.svg
  - lk-wordmark.svg
  - opengraph-image-bg.png
- - globals.css
- .env.example
- .eslintrc.json
- .gitignore
- .prettierignore
- .prettierrc
- app-config.ts
- components.json
- eslint.config.mjs
- next.config.ts
- package.json
- pnpm-lock.yaml
- postcss.config.mjs
- README.md
- tsconfig.json
- install.sh
- install.sh
- README.md
- requirements.txt
- server.py
.gitignore
README.md
start.sh

# CDN으로 사용하기

jsDelivr

jsDelivr는 공개 GitHub 리포지토리를 별도 설정 없이 CDN으로 즉시 서빙합니다. 버전과 파일을 고르면 웹페이지에 바로 붙일 수 있는 링크와 예시 코드가 만들어집니다.

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// repository documentation

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> **A voice-driven teleprompter that runs entirely on your laptop.**

Open a script, hit start and read out loud! The page scrolls under your voice, **word by word**, driven by NVIDIA's multilingual 600M-parameter speech model running locally. Read in English, Spanish, Japanese, or any of 35+ languages — the model detects the language automatically (or pin one with `STT_LANGUAGE`). Your voice never leaves the machine.

![The teleprompter home screen](https://raw.githubusercontent.com/ShayneP/local-teleprompter/main/assets/teleprompter.png)

## Quickstart

```bash
git clone <this repo>
cd local-teleprompter
./start.sh
```

That's it. Then open `http://localhost:3000`, pick a script, hit start, and read. Press **Ctrl-C** in the terminal to bring everything down.

On first run, `start.sh` will install dependencies — pulling `torch` and NVIDIA's NeMo toolkit takes a few minutes and several GB. Subsequent runs come up in seconds.

## Why local?

- **Zero cloud bill.** A teleprompter is a "20 minutes of mic" workload. That gets expensive fast at $0.01–0.05/min cloud STT pricing. Local is free.
- **No latency floor.** End-of-utterance to final transcript is consistently <150ms on Apple Silicon, around 100ms on a real GPU. Word-level streaming starts within ~80ms of speech.
- **Privacy.** Your voice and your script never leave the machine.
- **It's fun.**

## Requirements

- **macOS or Linux** (Apple Silicon, Intel Mac, or NVIDIA Linux)
- **Python 3.10+**
- [`uv`](https://docs.astral.sh/uv/) — install with `curl -LsSf https://astral.sh/uv/install.sh | sh`
- **Node 20+ and `pnpm`** — `npm i -g pnpm` or `brew install pnpm`
- **Homebrew** on macOS (used to install one binary if it isn't already on PATH)

A CUDA GPU is not required. On Apple Silicon the model runs on MPS automatically. CPU also works, just slower. GPU does work best though.

## Scripts

Scripts are stored in a local SQLite database at `frontend/data/scripts.db`. The DB is created on first launch and seeded with a sample script. You can:

- **Create**, **edit**, and **delete** scripts in the library view.
- **Import** any Markdown or plain text file (`.md`, `.markdown`, `.txt`). The first `#` heading becomes the title; the rest becomes the body.
- **Export** any script as Markdown.

The DB is just a regular SQLite file — open it with any SQLite tool, back it up by copying it, or move it elsewhere with `SCRIPTS_DB_PATH=/path/to/scripts.db`.

## How the cursor follows your voice

![The prompter view, highlighting words as you say them](https://raw.githubusercontent.com/ShayneP/local-teleprompter/main/assets/script.png)

Speech recognition gives you words. Turning those into the right *script position* — even when you stumble, skip a sentence, or re-read a paragraph — is the interesting part. The matcher lives in [`frontend/lib/teleprompter/position-tracker.ts`](frontend/lib/teleprompter/position-tracker.ts):

- **Forward-only** under normal flow. Each new spoken word scans an 18-word lookahead from the current cursor.
- **Bigram confirmation** for non-local jumps. A far match (3–17 words ahead) only commits if the *previous* spoken word also confirmed nearby — stops stopwords ("the", "is", "of") from yanking the cursor ten words ahead.
- **Tightly-scoped fuzzy matching.** Levenshtein-1, but only for words ≥ 5 characters. Short words must match exactly, so `the ↔ then` doesn't sneak through.
- **Auto re-anchor.** After 4 unmatched words in a row, scan a 6-word trailing window globally; commit a jump if ≥ 3 words align.
- **Double-click a word** to manually snap the cursor there. Pause freezes it; resume picks up wherever you start reading again.

If the matcher feels off for your style, the constants at the top of `position-tracker.ts` are the levers:

| Constant | Default | What it does |
| --- | --- | --- |
| `DEFAULT_LOOKAHEAD` | 18 | How many script words ahead a single spoken word can jump |
| `NEAR_JUMP` | 2 | Small jumps that don't need bigram confirmation |
| `BIGRAM_WINDOW` | 3 | How far back the prior-word confirmation looks |
| `REANCHOR_MISS_THRESHOLD` | 4 | Unmatched words in a row before re-anchor kicks in |
| `REANCHOR_WINDOW` | 6 | Trailing spoken-word window for re-anchoring |
| `REANCHOR_MIN_MATCHES` | 3 | Matches required to commit a re-anchor |

If you stall on mumbled words, bump `NEAR_JUMP` to 3. If the cursor jumps too aggressively, lower `DEFAULT_LOOKAHEAD` or raise `REANCHOR_MIN_MATCHES`.

## Tinkering

Most of the interesting parts:

- [`frontend/lib/teleprompter/position-tracker.ts`](frontend/lib/teleprompter/position-tracker.ts) — the matching algorithm.
- [`frontend/components/teleprompter/`](frontend/components/teleprompter/) — library, editor, and prompter UI.
- [`stt-server/server.py`](stt-server/server.py) — the speech-to-text server.
- [`agent/src/`](agent/src/) — the glue that hands audio to the model and transcripts to the browser.

## Credits

- **Speech model:** NVIDIA's [`nemotron-3.5-asr-streaming-0.6b`](https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b), a multilingual (35+ languages) cache-aware FastConformer-RNNT.
- **STT server scaffold:** [`fastapi-nemotron-speech-streaming`](https://github.com/ShayneP/fastapi-nemotron-speech-streaming).
- **Frontend starter:** [`livekit-examples/agent-starter-react`](https://github.com/livekit-examples/agent-starter-react).

## License

MIT — do whatever you want with it.