Home Assistant
add-on that uses openWakeWord
(demo on huggingface) for wake word detection over the wyoming
protocol on NVIDIA Jetson devices. Thank you to @ms1design for contributing these Home Assistant & Wyoming containers!
- Works well with
home-assistant-core
container on Jetson devices as well as Home Assistant hosted on different hosts - Use custom wake word's, pass model name as
OPENWAKEWORD_PRELOAD_MODEL
to preload custom model. For example you can findjetson
(jets_un
) wake word model included in/share/openwakeword
models directory. - Supports
*.tflite
CPU
wake word models - Supports
*.onnx
CUDA
wake word models [WIP]
Requires Home Assistant
2023.9
or later.
If you want to use docker compose
to run Home Assistant Core Voice Assistant Pipeline on a Jetson device with cuda
enabled, you can find a full example docker-compose.yaml
here.
name: home-assistant-jetson
version: "3.9"
services:
homeassistant:
image: dustynv/homeassistant-core:latest-r36.2.0
restart: unless-stopped
init: false
privileged: true
network_mode: host
container_name: homeassistant
hostname: homeassistant
ports:
- "8123:8123"
volumes:
- ha-config:/config
- /etc/localtime:/etc/localtime:ro
- /etc/timezone:/etc/timezone:ro
openwakeword:
image: dustynv/wyoming-openwakeword:latest-r36.2.0
restart: unless-stopped
runtime: nvidia
network_mode: host
container_name: openwakeword
hostname: openwakeword
init: false
ports:
- "10400:10400/tcp"
volumes:
- ha-openwakeword-custom-models:/share/openwakeword
- /etc/localtime:/etc/localtime:ro
- /etc/timezone:/etc/timezone:ro
environment:
OPENWAKEWORD_CUSTOM_MODEL_DIR: /share/openwakeword
OPENWAKEWORD_PRELOAD_MODEL: ok_nabu
volumes:
ha-config:
ha-openwakeword-custom-models:
Variable | Type | Default | Description |
---|---|---|---|
OPENWAKEWORD_PORT |
str |
10400 |
Port number to use on host |
OPENWAKEWORD_THRESHOLD |
float |
0.5 |
Wake word model threshold (0.0 -1.0 ), where higher means fewer activations. |
OPENWAKEWORD_TRIGGER_LEVEL |
int |
1 |
Number of activations before a detection is registered. A higher trigger level means fewer detections. |
OPENWAKEWORD_PRELOAD_MODEL |
str |
ok_nabu |
Name or path of wake word model to pre-load. The name of the model should match with name used during custom wake word model training. When changing this, it's also recommended to set WAKEWORD_NAME variable with same value for wyoming-assist-microphone container |
OPENWAKEWORD_CUSTOM_MODEL_DIR |
str |
/share/openwakeword |
Path to directory containing custom wake word models. Skip the trailing slash (/ ) |
OPENWAKEWORD_DEBUG |
bool |
true |
Log DEBUG messages |
Read more how to configure wyoming-openwakeword
in the official documentation:
Note
You can find a custom trained, example jetson
(jets_un
) wake word model in the custom models directory (/share/openwakeword
). To use it, set WAKEWORD_NAME
to jets_un
in appropriate containers.
The Home Assistant Community has trained numerous wake word models, as detailed in this GitHub repository. However, these models are specifically designed for use with CPU
.
To train a new wake word model for CPU
(*.tflite
) or cuda
(*.onnx
), you can follow @dscripka documentation or just jump to the point and use wake word training environment.
- Build
openWakeWord
from source based ononnxruntime
gpu
enabled container (currentlyopenWakeWord
is still usingtflite
models insteadonnx
) - Custom Wake Word Models training container using automatic synthetic data creation
Got questions? You have several options to get them answered:
- The Home Assistant Discord Chat Server.
- The Home Assistant Community Forum.
- Join the Reddit subreddit in
/r/homeassistant
- In case you've found an bug in Home Assistant, please open an issue on our GitHub.
- The NVIDIA Jetson AI Lab tutorials section.
- The Jetson AI Lab - Home Assistant Integration thread on NVIDIA's Developers Forum.
- In case you've found an bug in
jetson-containers
, please open an issue on our GitHub.
Note
This project was created by Jetson AI Lab Research Group.
CONTAINERS
wyoming-openwakeword:latest |
|
---|---|
Aliases | wyoming-openwakeword |
Requires | L4T ['>=34.1.0'] |
Dependencies | build-essential homeassistant-base python:3.11 |
Dockerfile | Dockerfile |
Images | dustynv/wyoming-openwakeword:latest-r36.2.0 (2024-04-30, 0.3GB) |
Notes | The openWakeWord using the wyoming protocol for usage with Home Assistant. Based on https://github.com/home-assistant/addons/blob/master/openwakeword/Dockerfile and https://github.com/rhasspy/wyoming-openwakeword |
RUN CONTAINER
To start the container, you can use jetson-containers run
and autotag
, or manually put together a docker run
command:
# automatically pull or build a compatible container image
jetson-containers run $(autotag openwakeword)
# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host openwakeword:35.2.1
jetson-containers run
forwards arguments todocker run
with some defaults added (like--runtime nvidia
, mounts a/data
cache, and detects devices)
autotag
finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.
To mount your own directories into the container, use the -v
or --volume
flags:
jetson-containers run -v /path/on/host:/path/in/container $(autotag openwakeword)
To launch the container running a command, as opposed to an interactive shell:
jetson-containers run $(autotag openwakeword) my_app --abc xyz
You can pass any options to it that you would to docker run
, and it'll print out the full command that it constructs before executing it.
BUILD CONTAINER
If you use autotag
as shown above, it'll ask to build the container for you if needed. To manually build it, first do the system setup, then run:
jetson-containers build openwakeword
The dependencies from above will be built into the container, and it'll be tested during. Run it with --help
for build options.