I’d like to know how AI/Machine Learning is being used with all the data gathered through HA Analytics. Is this data being mined to direct the improvement of HA?
There must be some patterns in all that data to identify some common combinations of integrations that could be used to put together some pre built automations that would benefit a large number of users.
I’d love to see how the data being collected is being used to benefit the community.
Perhaps more than 1/3 of users would opt in if it was clearer what impact it has on the roadmap.
Hah, it’s not just New Zealand. I live in Canada and had the same problem. Seems to be a general issue with the Whisper model, however. IDEALLY there would be a (better… which may mean larger…) language model integrated with the voice recognizer that could correct such things based on context.
Two possible short-term fixes:
Try a larger Whisper model. If you are on a Rasp Pi 4 or earlier that may not be feasible, but perfectly possible on larger hosts (I use a NUC personally…).
Create an intent that includes “whole light” as a possible “spelling” of “hall light”. Your users will never know
