Why Run a Voice Assistant on the Edge?

Running speech‑to‑text and intent detection locally gives you:

Zero latency – no round‑trip to the cloud.

Privacy – audio never leaves the device.

Offline reliability – your assistant works even when the internet is down.

In this tutorial we’ll stitch together OpenAI’s Whisper (small model) for transcription, a tiny TensorFlow Lite intent classifier, and a real‑time audio pipeline that lives entirely on a Raspberry Pi 4 (2 GB or more). By the end you’ll have a Python script that listens for commands like “turn on the lamp” and executes a local function instantly.

What You’ll Need

Item Reason

Raspberry Pi 4 (2 GB+) with Raspberry OS (64‑bit) Provides enough RAM for Whisper‑small

Micro‑USB or USB‑C microphone Captures audio

Python 3.10+ Modern language features

ffmpeg Required by Whisper

git , pip , virtualenv Standard development tools

Optional: GPIO‑controlled relay To demonstrate a real command

Tip: If you’re using a Pi Zero, swap Whisper for a lighter…