Use events and commands to control custom onboard leds and buttons. Can be used to communicate with an external Python script via a WebSocket API running in a container alongside LVA.
Refactor the README to improve clarity by replacing the "Usage" section with a dedicated "Requirements" section. This includes:
- Adding specific hardware requirements (Microphone, CPU, Memory, Storage, OS).
- Updating recommended hardware configurations for better readability.
- Clarifying compatibility notes regarding Raspberry Pi Zero 2W and Respeaker Lite.
## Summary
- Introduces configurable wake word and stop word sensitivity
- Adds UI-controllable thresholds for wake word detection
- Refactors wake word loading and handling logic
- Improves audio preprocessing and runtime behavior
## Key Features
- Per-wake-word sensitivity configuration (Wake Word 1 & 2)
- Configurable stop word sensitivity
- Fine-grained numeric control (0.0 – 1.0, step 0.001)
- Sensitivity values exposed as Number Entities for Home Assistant
- Persistent storage of user-defined sensitivity values
## Wake Word Handling
- Support for model-specific default thresholds (`probability_cutoff`)
- Automatic fallback to defaults if no user value is set
- Separate thresholds for:
- Wake Word 1
- Wake Word 2
- Stop Word
- Unified handling for MicroWakeWord and OpenWakeWord models
## UI / API Integration
- Adds new Home Assistant entities:
- `WakeWord1SensitivityNumberEntity`
- `WakeWord2SensitivityNumberEntity`
- `StopWordSensitivityNumberEntity`
- Entities support:
- Live updates
- Persistence via preferences
- Synchronization with runtime state
- Pushes updated values to Home Assistant on startup
## Refactoring
- Extracted wake word logic into `wake_word.py`
- Model discovery
- Model loading
- Stop word handling
- Simplified `__main__.py` by delegating wake word responsibilities
- Improved separation between configuration and runtime state
## Additional Changes
- Improved debug logging across initialization and runtime
## Impact
- Enables fine-tuning of wake word detection accuracy
- Reduces false positives and missed triggers
- Improves usability via UI-based configuration
- Provides better flexibility across different environments and microphones
## WebRTC Auto Gain & Noise Suppression
This PR adds support for WebRTC Auto Gain and Noise Suppression as previously implemented in the Wyoming Satellite project.
### What's New
Two new entities have been created a number slider for gain and another one for noise suppression. The processing happens inside of the `webrtc.py` file and is implemented in the `__main__.py` file's `process_audio` function. The slider for gain has a limit of 0-31 and noise suppression has a limit of 0-4.
The Auto Gain and Noise Suppression persist through restarts and are saved as preferences. The values are dynamically chnged without needing a restart.
CLI flags called `--mic-auto-gain` and `--mic-noise-suppression` have also been added.
> When both values are 0, WebRTC processing is bypassed entirely with no performance overhead.
Closes#25
### Testing
When saving the audio recorded by LVA there is a noticeable increase. The following two files have been recorded with similar audio being played through them with these results (Gain-31 and NS-4):
| Metric | With AGC+NS | Without |
|---|---|---|
| Max amplitude | 0.329 | 0.054 |
| RMS amplitude | 0.008905 | 0.002862 |
| Volume adjustment needed | 3.034x | 13.479x |
| Rough frequency | 916 Hz | 705 Hz |
Introduce a new `--output-only` command-line flag and corresponding `ENABLE_OUTPUT_ONLY` environment variable. This allows users to run the assistant in output-only mode, where it only supports announcements. The change includes updates to configuration examples, documentation, and the Docker entrypoint script.
* Change Client-Name: The client name inside LVA is not capable of having spaces in the name. Fixed the example.
* Add first version of Docker-Compose for developers
* Add variable for network-interface and auto detection by default
* Added autodetection for the MAC-Address based on the detected or specified network-interface.
* Switched from listening on all IP-Addresses to the IP of the default interface, usually u set the correct network-interface and it will automatically detect the right IP-Address.
* Added missing variables, fixed variables names
* Fixed not working variables for example sound-files.
* Moved the auto-name creation from shell to python. The name is no longer mandatory, it will be generated if no name is given.
