Speech Practice Partner

Adpirs — Sat, 03 Oct 2026 21:44:09 +0000

What I Built

Most voice assistants decide you've finished speaking after about a second of silence. For someone who stammers, is nervous about speaking, or is searching for words (after a stroke, for example), that means being cut off again and again. It makes practising out loud feel worse, not better.

So I built Speech Practice Partner, a patient conversation partner that never interrupts. You pick a topic you enjoy, press one big button and just talk. It waits as long as you need (you choose anywhere from 2 to 15 seconds of quiet), then replies in one or two short, gentle sentences. It never finishes your sentences, never corrects your grammar and never comments on pauses or repetition.

I built it for anyone and everyone, who gets anxious speaking to people and wants a low-pressure place to practise.

Things I cared about:

Calm and simple: one screen, one button, a soft orb that shows whether it is listening, hearing you, thinking or speaking.
Private: everything runs on the laptop and nothing goes to the cloud. Only the written transcript and a few numbers are saved, and your voice is never recorded. One button deletes everything.
Progress without pressure: a Progress page shows personal trends (pause length, pace, words per session). They are framed as trends, not scores, and the numbers are hidden during a session by default.

Demo

Video Link :https://youtu.be/UPSXFH25tTc?si=QE1RDLcW4migRK6D

The app has a --demo mode that previews the whole interface with synthetic sample data and a pretend conversation. Any trend charts in the demo come from that synthetic data and are not real people's results.

How I Built It

The whole pipeline runs locally:

Mic → Silero VAD → faster-whisper → Gemma (via Ollama) → Piper voice

Silero VAD detects when you start and stop talking. I set the end-of-speech silence window myself, which is the heart of the project.
faster-whisper (small.en) transcribes locally. I prompt it to keep repetitions and fillers instead of "cleaning them up".
Gemma (gemma3:4b, open weights, run through Ollama) is the conversation partner. A short system prompt keeps it warm, brief and non-corrective.
Piper speaks the replies, with an adjustable slower voice.
TabPFN (optional, local) forecasts the next session's pause length and speaking rate from past sessions. It is backtested against a naive baseline, and it needs at least 8 real sessions before it will forecast. [Add your backtest result here once you have real sessions, or delete this line.]
Flask + plain HTML/CSS/JS make up the interface. There are no frontend frameworks and no CDN, so it works fully offline. The server only listens on 127.0.0.1.

I started from a terminal-only prototype and turned it into a simple browser app: settings inside the app, friendly error messages (like "Open the Ollama app and try again"), a session you can end at any moment, and dark mode.

Why Does Open Innovation Matter?

Control over the one setting that matters. With a closed voice API, I can't change how long it waits before deciding you're done. With open components I could set that window to match the person, and tune it with them.
Privacy. A person practising something vulnerable shouldn't have to send their voice to someone else's servers. Because every model runs locally, their speech never leaves the laptop.
Free, unlimited practice. Confidence builds with repetition, and nobody has to worry about per-minute API costs.
Tunable to the person. The prompt, voice speed and wait time can all be adjusted after each session.

Prize Categories

Gemma

Intro...

Adpirs — Thu, 01 Oct 2026 17:57:21 +0000

Hi all, I am new to dev and I really like the UI of this app gives you that gamer like feeling when you see the text...lol (^_^)