# microWakeWord-Trainer-Nvidia-Docker

> Self-hosted Docker app that trains wake word models using NVIDIA GPU acceleration with a Vue 3 web UI for sample management and satellite integration.

- **Category:** AI
- **Latest version:** v47.3
- **Open source:** oss
- **Languages:** JavaScript, Python, HTML, Shell
- **Platforms:** Docker
- **Tags:** Voice Assistant, Nvidia, Cuda, Docker, Stt, Text To Speech, Wake word, microWakeWord, openWakeWord, nanoWakeWord, Tater

## Description

microWakeWord Trainer is a self-hosted Docker application for training custom wake word models (microWakeWord, openWakeWord, NanoWakeWord CNN/GRU) using NVIDIA GPU acceleration. It provides a reactive Vue 3 + TypeScript web UI for managing positive and negative audio samples, reviewing captured audio from Tater Native or ESPHome satellites, and running automated training loops with local speech-to-text (Faster Whisper or Parakeet ONNX). The trainer generates text-to-speech samples via multiple providers (OmniVoice, Qwen3-TTS, MOSS-TTS-Nano, Piper), normalizes all audio to a standard sample rate and bit depth, and publishes trained wake word bundles (JSON plus .tflite/.onnx models) that Tater Native satellites can load live without firmware changes. It runs via a single Docker container with --gpus all, exposes the UI on port 8789 (configurable via REC_PORT), and persists all data in a mounted /data volume. The project includes a separate Docker image for RTX 50-series (Blackwell) GPUs using a community-built TensorFlow wheel (CC BY-NC 4.0). No license file is present in the repository.

## Links

- [Homepage](https://github.com/TaterTotterson/microWakeWord-Trainer-Nvidia-Docker)
- [Website](https://taterassistant.com)
- [Docker](ghcr.io/tatertotterson/microwakeword)
- [GitHub Repository](https://github.com/TaterTotterson/microWakeWord-Trainer-Nvidia-Docker)

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Source: https://selfhost.directory/project/microwakeword-trainer-nvidia-docker