When you get sick of tripping over things in the dark you may want “Jaysus turn on the lights”
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A simple “let there be light” does the job in my kitchen. Well established and still working 
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I agree with @tobol . I’d never choose to use “Okay Nabu”. I’d much rather use my own choice of wakeword(s).
MUCH better to ask for effort to improve the whole voice recognition environment across multiple words, languages and accents. That I’d happily support and contribute my time to. But “Okay Nabu” - no thanks.
I also agree with @Hedda that voice contributions, if being made public, should be truely anonymous.
Otherwise you’re going against the HA personal privacy principle in essence, even if you’ve asked and got permission.
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Appreciate all the hard work thats going into this. And I get it "Okay Nabu” is a distinct enough phrase for detection. But for the love of god, please lets drop this as the default intent. Especially with the rumored voice devices coming out. Its truly an awful choice, with all due respect 
And you guys just seem to be going down hard in the rabbit hole here to double down on this as the default choice.
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It feels strange to me that the first wakeword to be crowd-sourced is one that is associated with the for-profit entity, rather than the Open Home Foundation or Home Assistant. It feels like the priority is being placed in the wrong place and it sends the wrong message.
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would you rather have “Okay Open Home Foundation” instead?
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I’d rather have had a vote on it
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@ut666 @carolinasnowbird @infinitebagel you guys should read the entire thread, in particular this post Help us make voice better in under a minute - #22 by synesthesiam
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Personally I favour “hey f***wit, turn on the lights”
But I suspect I’ll have to train that one myself.
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Until of course home assistant achieves world domination, and the commercial players want to emulate it. “Buy our product and get all the advantages of home assistant, plus these added features, on a simple monthly subscription”
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Oh damn that’s cool thank you!
1st: big thank you for the efforts
FWIW: Nabu == Germany’s biggest and oldest NGO. Continuously present in media, I doubt German users want to call their HASS “Nabu” Wir über uns - NABU
+1 for custom wake words. No worries training it myself as it only has to listen to me and my family as opposed to a trillon different accents and dialects. In fact, I want HASS to only listen to me and my family … just my 2ct
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I have no issue with Nabu, despite a German background.
I don’t understand the whole fuss anyhow.
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It’s a human thing (and seems to become even worse as we are ‘evolving’): complaining, criticizing, …
In this case also: they probably didn’t read the relevant postings…
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Calling your voice assistant with the same name as an environmental association is a boss move.
Both are looking out for the environment - one of them takes care of the nature around you, while the other takes care of the environment by making sure you’re not wasting electricity because you don’t want to get up to flip a switch 
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From a dialect we speak in Singapore (originates from China and Taiwan) called Hokkien.
What is the status on adding an all-in-one training notebook for microWakeWord (mWW) model training so that we can more easily can train our our own microWakeWord models?
PS: For the openWakeWord model training there is a fully scripted and automated Google Codelab notebook but I understand that might not work for microWakeWord (mWW) model training which takes longer and require more resources?
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Indeed thanks for pointing this out Hedda. I was not aware it’s a different wake word model. This has suddenly become a very high priority ask.
FYI, some/most posts that questioned the choice of default wake-word on official Home Assistant voice hardware where moved to a new thread seperating that discussion (though it still a very much on-topic here), see:
@synesthesiam, I think I understand it now! So microWakeWord already has “okay nabu”, “hey Jarvis” and “Alexa” models. But from the three, “okay nabu” has the worst false-accept/false-reject rate, so this is to have a dataset big enough to improve the model. Am I right?
If it’s that simple, I can see the benefit and the choiceability here. Thanks!