mirror of
https://github.com/dscripka/openWakeWord.git
synced 2026-08-27 18:17:20 -04:00
40 lines
2 KiB
Markdown
40 lines
2 KiB
Markdown
# Examples
|
|
|
|
Included are several example scripts demonstrating the usage of openWakeWord. Some of these examples have specific requirements, which are detailed below.
|
|
|
|
## Detect From Microphone
|
|
|
|
This is a simple example which allows you to test openWakeWord by using a locally connected microphone. To run the script, follow these steps:
|
|
|
|
1) Install the example-specific requirements: `pip install pyaudio`
|
|
|
|
2) Run the script: `python detect_from_microphone.py`.
|
|
|
|
Note that if you have more than one microphone connected to your system, you may need to adjust the PyAudio configuration in the script to select the appropriate input device.
|
|
|
|
## Capture Activations
|
|
|
|
This script is designed to run in the background and capture activations for the included pre-trained models. You can specify the initialization arguments, activation threshold, and output directory for the saved audio files for each activation. To run the script, follow these steps:
|
|
|
|
1) Install the example-specific requirements:
|
|
|
|
```
|
|
# On Linux
|
|
pip install pyaudio scipy
|
|
|
|
# On Windows
|
|
pip install PyAudioWPatch scipy
|
|
```
|
|
|
|
2) Run the script: `python capture_activations.py --threshold 0.5 --output_dir <my_dir> --model <my_model>`
|
|
|
|
Where `--output_dir` is the desired location to save the activation clips, and `--model` is the model name or full path of the model to use.
|
|
If `--model` is not provided, all of the default models will be loaded. Use `python capture_activations.py --help` for more information on all of the possible arguments.
|
|
|
|
Note that if you have more than one microphone connected to your system, you may need to adjust the PyAudio configuration in the script to select the appropriate input device.
|
|
|
|
## Benchmark Efficiency
|
|
|
|
This is a script that estimates how many openWakeWord models could be run on on the specified number of cores for the current system. Can be useful to determine if a given system has the resources required for a particular use-case.
|
|
|
|
To run the script: `python benchmark_efficiency.py --ncores <desired integer number of cores>`
|