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Live Kaiwa – real-time Japanese conversation support

Live Kaiwa – real-time Japanese conversation support

by diasks2·Mar 12, 2026·2 points·1 comment

AI Analysis

●●SolidNiche GemSolve My Problem

Otter.ai for Japanese expats: transcribes, translates, and summarizes civic meetings in real time.

Strengths
  • Running summary feature helps track long, complex discussions where context drifts.
  • Pay-as-you-go pricing without subscription lock-in is refreshing for utility tools.
  • Context Q&A lets you catch up on missed details without interrupting speakers.
Weaknesses
  • Browser microphone reliance means background noise in meetings could degrade accuracy significantly.
  • Niche appeal limits growth; mostly useful for foreign residents living in Japan.
Category
Target Audience

Foreign residents in Japan, Japanese language learners

Similar To

Otter.ai · DeepL · Google Translate

Post Description

I live in a rural farming neighborhood in Japan.

Day-to-day Japanese is fine for me. But neighborhood meetings were a completely different level.

People speak fast. There's local dialect. Someone references a flood from 1987, a land boundary dispute from 1994, and three people I've never met but everyone else knows. I would walk out feeling like I understood maybe 5% of what happened.

So I built a tool for myself to help follow those conversations.

Live Kaiwa listens to Japanese speech and, in real time, shows:

* Japanese transcription * English translation * a running summary of what's being discussed * suggested responses you can say back

The idea is to help you stay oriented in complex conversations.

You can try it here: https://livekaiwa.com

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How it works

When you start a session, the browser microphone captures the conversation and streams audio.

The pipeline looks roughly like this:

1. Audio streaming - Browser microphone → WebRTC → server

2. Speech to text - Kotoba Whisper runs a fast first pass transcription.

3. Multi-pass correction - Buffered audio is re-transcribed with higher accuracy and replaces earlier text.

4. LLM processing - Each batch of transcript is sent to an LLM that generates: English translations, summary bullets, and suggested replies (with TTS)

5. Live UI updates - Everything streams back to the browser in (mostly) real time.

Session data stays in the browser, nothing is stored server-side.

Why I built it, in short: even if you speak Japanese reasonably well, fast, multi-person discussions can become overwhelming. Seeing the conversation transcribed and summarized helps.

Similar Projects

Open Source●●Solid

DeskMic a Rust based hyper-light continuous transcriber/AI summarizer

This nails the ugly, practical bits most toy projects skip: WASAPI loopback for Teams audio, a Silero VAD ring buffer to only save speech segments, and robust sleep/device-recovery with exponential backoff. It combines local whisper-rs transcription with optional Azure-based pipelines and scheduled ACS email summaries — a focused, pragmatic tool for people who actually need continuous meeting capture without sending everything to a SaaS.

Niche GemWizardry
varunr89
103mo ago