4.1 / 5

Live Captioner

Real-time captions for any audio playing on your computer

Serious

Privacy

The Problem

Not all audio/video has captions; auto-captions are often inaccurate

Current Solutions (Not Great)

YouTube auto-captions (inaccurate), paid services (expensive), manual transcription (slow)

Who Needs This

Deaf/HoH users, non-native speakers, people in noisy environments, students in lectures

Video calls, online lectures, YouTube videos, podcasts—not everything has good captions, and auto-generated ones are often wrong. Live Captioner captures any audio playing on your system (or from your mic) and generates accurate captions in real-time. It's smarter than YouTube's auto-captions because it uses context, corrects itself, and can handle technical jargon and accents better. Essential for deaf/HoH users, useful for anyone in a noisy environment or learning a language.

Honest Take

The accessibility angle is strong but this market is pretty saturated with Google Live Transcribe, Otter.ai, and built-in OS features. Your privacy/local-first pitch could work for corporate environments worried about confidentiality, but competing with free OS-level features is tough.

Monetization Ideas

Ways to turn this into revenue

Freemium

Free basic, $5-15/mo for pro

Subscription

$5-29/month or $49-199/year

Donations / Tip Jar

$5-50/month from grateful users

Features

Key features that make this app valuable

Capture system audio or microphone
Real-time caption overlay
Speaker diarization (who said what)
Technical jargon handling
Accent adaptation
Caption styling (size, position, colors)
Transcript export
Translation mode (caption in different language)

Build Prompt

Use this prompt with an AI assistant to start building

Build a React PWA called 'Live Captioner' using WebInfer and audio capture. Use getDisplayMedia({ audio: true, video: true }) for system audio (video track can be ignored). Alternative: getUserMedia for mic input. Connect audio stream to AudioWorklet for chunking (e.g., 3-second segments with 1-second overlap). For each chunk: 1) Run Web Speech API for base transcription, 2) Use AI to correct and enhance. Use generateObject to return { correctedText: string, confidence: number, speaker: number, isFinal: boolean }. Display captions in floating overlay (position: fixed, bottom of screen). Caption styling controls: font size, background opacity, text color. Rolling transcript view. Speaker colors for diarization. 'Translation mode' runs translation after transcription. Export transcript with timestamps. Shortcut keys: toggle captions, increase/decrease size. Accessibility: high contrast mode, dyslexia-friendly font option.

Score Breakdown

Pain