Kommz Gamer

Real-time voice translation for gaming

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August 30, 2026 I built a real-time voice translation app for gaming - here's what I learned from a year of solo dev

I've been building Kommz Gamer for the past year, but the idea is actually 10+ years old. Back then I was a pure geek trying to learn programming as a self-taught dev, but I eventually gave up on it.

Last year I was playing Valorant and met an English speaker and a Spanish player in a match. Impossible to communicate. That's when this project came back to me. I told myself: "Now there's AI, let's try it. I have nothing to lose." Long story short, I got addicted. 13-16 hours a day for 4 months, and I had a working version online.

What it does:

🌍 Real-time voice translation across 20+ languages (Deepgram Nova-2)

Transcribes your voice, translates it, and speaks it back - all in a few seconds.

🎮 Auto game detection in 2-3s (audio fingerprint) with automatic profile switching

Identifies the game and applies the right audio profile automatically.

🎧 Voice Focus V3: voice isolation, noise reduction, auto calibration

Filters out keyboard noise, background music, and other players' voices.

📺 OBS overlay for streamers

Displays translations as subtitles on your stream.

🧬 Optional voice cloning (your own voice, translated into any language)

Record 30 seconds of your voice - your teammates hear YOU speaking their language.

🐟 Fish Audio Premium → a second TTS engine option, bring your own API key

More expressive voices with emotional markers.

⚡ <300ms latency in Turbo Mode (Edge TTS only → voice cloning trades speed for quality)

Fast mode for competitive play, quality mode for voice cloning (~1.5s GPU synthesis).

🛡️ Anti-cheat safe → no DLL injection, no memory reading, works like OBS/Discord

Compatible with Vanguard, Ricochet, and BattleEye.

📱 Mobile Command Center to control everything from your phone

Change language, adjust mic sensitivity, all from your phone.

What I learned building this:

🐍 Python monolith → modular Flask architecture

Refactored from a ~11K line monolith into 13 modular Flask blueprints (~81 routes). That was the biggest technical challenge.

🔨 Nuitka onefile build

Compiling Python to native C. qt.conf, PySide6 DLLs, memory management - the Windows build pipeline was one of the hardest parts.

🎧 Audio on Windows is a nightmare

WASAPI loopback, CABLE Input, Voicemeeter, ASIO - each setup is different. That consumed most of the year.

🧠 Voice cloning pipeline

XTTS v2 on Modal GPU cloud, direct /v1/synthesis endpoint. Benchmarked live: ~1.2-1.6s GPU synthesis, ~4-6s round-trip total, WER 0-7% in French.

📊 Live benchmarks

- STT (Deepgram Nova-2): ~370ms

- Translation (DeepL): ~320ms

- TTS (XTTS Modal GPU): ~1.2-1.6s

- WER: 0-7% (tested in French, clear speech)

⚙️ Tech stack

Python + Flask (13 blueprints, ~81 routes), Nuitka onefile build, HTML/JS frontend in PyWebView, Deepgram STT, DeepL translation, Edge TTS + XTTS voice cloning on Modal GPU, WASAPI loopback + CABLE Input for Windows audio capture.

🎥 Demo video (French audio with English subtitles): https://www.youtube.com/watch?v=6BZbSO--iCY

The project is open-source, split into two repos:

🖥️ Kommz Gamer (the desktop app): https://github.com/KommzAI/Kommz-Gamer

🐟 Kommz Voice (the voice cloning engine): https://github.com/KommzAI/Kommz-Voice

⚡ Free 24h trial (no card, full access), then plans starting at €10/month: https://kommz.fr

💬 Discord: https://discord.gg/XpVCYktJ4B

🚀 Also on Product Hunt: https://www.producthunt.com/products/kommz-gamer-v5-3

Solo dev from France, built everything alone. AGPLv3 - contributions welcome. AMA about the monolith refactoring, Nuitka build, or the Windows audio pipeline.

3 Comments

  1. 1
    The technical depth is impressive, but I’m most curious about the core adoption signal. Is real-time communication during competitive games the main reason users stick with Kommz, or are streamers/voice cloning becoming equally strong use cases?
    1. 1

      Great question! For now I don't have paying clients yet - I just launched the product and I'm building the user base.

      Here's what I'm seeing so far:

      Competitive gaming = the main use case. That's what I built the product for originally - thion problem in ranked is real. Turbo Mode <300 = the segment generating the most interest when I showcase the product. The OBS overlay + voice cloning combo is what gets people excited. But I don't have hard numbers yet.

      Voice cloning = the feature getting the most positive feedback. People are impressed by the possibility of speaking in another language with their own voice.

      For now it's mostly qualitative feedback (Reddit). Concrete numbers will come withhe first paying users.

      Thanks for asking - it's making me think about what I should measure first!

      1. 1
        That makes sense. The gap between qualitative excitement and the first real paying-user behavior will probably tell you much more about which use case actually matters.

About

Playing Valorant last year, I met an English and Spanish player. Couldn't communicate at all. This 10+ year old idea came back — I was a self-taught dev who gave up back then. With AI available now, I tried again. 13-16h