Configuration

Rero Core is configured via a single config.ini file passed to each executable:

./bin/rero_server ./conf/config.ini

Executables expect the path to this file as their first argument.

Default configuration

A typical config.ini looks like:

[server]
host=0.0.0.0
port=50052
paDeviceIndex=-1

[model]
path="./models/vosk-rpi-model/"

[nlu]
model_path="./models/nlu/nlu_engine_music/"

Selecting the audio device

To list audio devices and their indices:

python3 -m sounddevice

Pick the desired input device index and set paDeviceIndex accordingly, then restart the Rero Core service (for systemd-based installs):

sudo service rerocore restart

Important: Any change to config.ini requires a restart of the core service for the changes to take effect.

Custom speech recognition vocabulary

To improve recognition accuracy in a narrow domain, define a custom vocabulary file:

Create models/vocab.txt with one term per line.

Update the model section:

[model]
path="./models/vosk-rpi-model/"
vocab_path="./models/vocab.txt"

Restart the service:
```
sudo service rerocore restart
```

Custom NLU models

You can train a new NLU model using the Snips NLU toolkit, following their CLI documentation. Once trained, point Rero Core to the model directory:

[nlu]
model_path="/path/to/trained/model"

Models trained on x86 can be copied to ARM devices (like Raspberry Pi) and used directly for inference.

Configuration Parameters

The following table lists all available configuration parameters, their section, and default values as read by the rero_server executable.

Section	Parameter	Type	Default Value	Description
`server`	host	string	`0.0.0.0`	gRPC bind address.
`server`	port	string	`50051`	gRPC port. Note: The example above uses `50052`.
`server`	headless	bool	`false`	If `true`, the Audio and Text-to-Speech services are not registered.
`server`	paDeviceIndex	int	`-1`	PortAudio input device index. `-1` selects the system default input device.
`server`	paOutputDeviceIndex	int	`-1`	PortAudio output device index.
`server`	denoising	bool	`false`	Enable audio denoising on the input stream.
`server`	storeAudio	bool	`false`	Enable storing audio streams to disk.
`server`	storeAudioPath	string	`""`	Path to store audio files if `storeAudio` is `true`.
`model`	path	string	`./models/vosk-rpi-model`	Path to the speech recognition model (e.g., Vosk model).
`model`	use_whisper	bool	`false`	If `true`, use the Whisper model for speech recognition. If using whisper, model path must be set to a whisper.cpp model.
`model`	vad_path	string	`./models/vad/silero_vad.onnx`	Path to the Voice Activity Detection (VAD) model.
`model`	vocab_path	string	`""`	Path to a custom vocabulary file for better recognition accuracy.
`nlu`	model_path	string	`./models/nlu/nlu_engine_music`	Path to the trained Natural Language Understanding (NLU) model directory.
`tts`	voice_path	string	`./models/tts/mycroft_voice_4.0.flitevox`	Path to the Text-to-Speech (TTS) voice model.
`tts`	use_ssml	bool	`false`	Enable SSML (Speech Synthesis Markup Language) support.
`tts`	use_larynx	bool	`false`	Use an external Larynx server for TTS.
`tts`	larynx_address	string	`http://localhost:5002`	Address of the Larynx TTS server.
`tts`	noise_scale	float	`0.667`	Parameter to control sample variability (noise/speaker difference).
`tts`	length_scale	float	`1.0`	Parameter to control speaking speed (1.0 is normal).
`hotword`	mel_model_path	string	`./models/hotword/logmelcalc.tflite`	Path to the hotword detection mel-spectrogram TFLite model.
`hotword`	base_model_path	string	`./models/hotword/baseModel.tflite`	Path to the hotword detection base TFLite model.
`hotword`	folder	string	`./models/hotword/hotwords`	Folder containing trained hotword embeddings.
`hotword`	threshold	float	`0.8`	Confidence threshold for a detected hotword to be accepted.