100 Table of Contents/Projects.md → Tools & Software
migration
home-assistant
project
esp32
architecture
minimax
voice
ai
showcase
0.66
false
324fa7828911
2026-10-08
project
voice
ai
showcase
MiniMax Voice
API integration (MiniMax T2A, Speech-to-Text)
Python standard-library services
Docker and Docker Compose
Audio DSP (PCM decode, linear resampling)
MQTT and Snapcast
Benchmarking and A/B measurement
MiniMax cloud APIs
OpenRouter Whisper
faster-whisper
piper TTS
Snapcast
Home Assistant
Archify
NixOS
MiniMax Voice — Overview
💡 What is this project?
A migration of the Jervis home voice assistant to MiniMax cloud speech
services, while keeping a working local fallback so the house keeps working
without internet.
Wake-word detection stays on the local machine. Only the spoken command is sent
to the cloud. This keeps cost low and keeps the continuous microphone stream
private.
The assistant hears the wake word, transcribes the spoken command, decides an
intent with an LLM, calls a tool, and speaks the reply through the house
speakers.
🌟 Key Highlights (Portfolio & Employment)
Concept: Replace a heavy local speech model with a cloud API, without ever
losing voice input when the internet is down.
Tools & Skills Showcase: MiniMax and OpenRouter APIs, Python standard
library, Docker, MQTT, Snapcast, audio resampling, drop-in service
compatibility, graceful fallback design, reproducible benchmarks.
Practical Value: Frees a few hundred MB of RAM on the home server, improves
voice quality, and keeps the house working during outages.