Sensitity to 0.1 to prevent false positives and trigger_level to 10 to prevent Mycroft to unintentionally activate.
Then I reload the config with:
mycroft-config reload
And finally lauch the client with:
mycroft-cli-client
Now, with my model and my training (don’t forget that I have done the “precise-train-incremental” training too), the detection of my wakeword is very inaccurate. When clapping in my hand, the client detect my wakeword.
Am I the only one, who can’t make an accurate model ?
Execute precise-listen <wake-word>.net -d <wake-word>/not-wake-word while you are watching a film or a series on Netflix or whatever
Execute precise-listen <wake-word>.net -d <wake-word>/not-wake-word and let it runs for days so that all spurious activations due to normal noises and sounds in the house (flapping doors, appliances, people’s speeches etc) will be automatically inserted in the not-wake-word folder
Training
Use 1000 or 2000 epochs, e.g. precise-train -e 1000 <wake-word>.net <wake-word>/
Copy all the wav files from wake-word folder to the test/wake-word folder, the same for the not-wake-word
Training steps
Collect and train with wake-word
Add not wake-word similar to the wake-word recorded and train again
Incremental train with the bunch of long audio
Add not wake-word registered during a film or due to a “home noise” and train again
Thanks for sharing your experience with me. Have you done some tests with the accuracy that your wakeword gives to you ? If you try to run the command: precise-test with your wakeword, what is the statistics of it ?