Mycroft wake word plugin for Vosk
pip install ovos-ww-plugin-vosk
Add the following to your hotwords section in mycroft.conf
"listener": {
"wake_word": "hey_computer"
},
"hotwords": {
"hey_computer": {
"module": "ovos-ww-plugin-vosk",
"listen": true
}
}
replace hey_computer
with your wake word and thats all!
a model wil be automatically downloaded for configured language
Some wake words are hard to trigger, usually if missing from the language model,
eg, hey mycroft
is usually transcribed as hey microsoft
,
by default this plugin will check for the wake word name, but the keyword can be configured in a number of ways
model_folder
- full path to a vosk model, optional, will be automatically downloadedlang
- lang code for model, optional, will use global value if not set. only used to download modelsdebug
- if true will print extra info, like the transcription contentsrule
- how to process the transcript for detections, see examples belowtime_between_checks
- the length in seconds between inferences, must be between 0.2 and 3full_vocab
- use the full model vocabulary for transcriptions, if false (default) vosk will run in keyword modesamples
- list of samples to match the rules against, optional, by default uses keyword name "listener": {
"wake_word": "hey_computer"
},
"hotwords": {
"hey_computer": {
"module": "ovos-ww-plugin-vosk",
"listen": true,
"full_vocab": true,
"rule": "equals",
"debug": true,
"samples": ["hey computer", "a computer", "hey computed"],
"model_folder": "/home/user/Downloads/vosk-model-small-en-us-0.4",
"time_between_checks": 0.6
}
}
You can define different rules to trigger a wake word
contains
- if the transcript contains any of provided samples equals
- if the transcript exactly matches any of provided samples starts
- if the transcript starts with any of provided samples ends
- if the transcript ends with any of provided samples fuzzy
- fuzzy match transcript against samplesTIP: enable debug
flag and check logs for what is being transcribed, then finetune the rule and samples
Each wake word must fit in 3 seconds, which is the length of audio the model parses at a time
You can try to improve performance by tweaking time_between_checks
, Lower values will decrease performance, higher values will decrease accuracy, default value is 1.0
set full_vocab
to transcribe all known words before applying detection rules, by default this is false and the plugin will only look for the wake word samples, depending on wake word this may improve or decrease accuracy
A single model per language can be used to check for multiple keywords at once
for example to replace the default wake words
"hotwords": {
"hey mycroft": {"active": false},
"wake up": {"active": false},
"hey xxx": {
"module": "ovos-ww-plugin-vosk-multi",
"listen": true,
"wakeup": true,
"keywords": {
"hey mycroft": {"samples": ["hey mycroft", "hey microsoft", "hey minecraft"], "rule": "fuzzy"},
"wake up": {"wakeup": true}
}
}
you can load any number of languages side by side
"hotwords": {
"hey_xxx": {
"module": "ovos-ww-plugin-vosk-multi",
"listen": true,
"full_vocab": false,
"keywords": {
"hey mycroft": {"samples": ["hey mycroft", "hey microsoft", "hey minecraft"], "rule": "fuzzy"},
"hey neon": {},
"hey computer": {},
"hey jarvis": {},
"computador": {"lang": "pt"},
"jarbas": {"lang": "pt"}
}
}