I found the module that's in the smart speaker that I talked about in the last post. It's here in quantity one for US$15. There isn't a whole lot in the way of other projects that use this module, but the manufacturer has a nice GitHub page with all of the chipset info on it, and I can copy the schematic of the smart speaker module (which looks like a handful of resistors and inductors). It looks like the most I'll have to do is set up the bare module with support parts, wire up a USB-A female connector, and load openWRT through a flash drive. 

I've been thinking more and more about implementing hierarchal clustering, which is all about finding the most connected pairs with the most similarities. However, the distance formula for single-link clustering implies that the most connected nodes will have the smallest numerical values attached to them. Before, I was increasing the value of emotion linkages that were find together, like finding 'relaxation' and 'joy' and connecting the two together. 

Playing around, I inverted it, so that the only nodes that see their numerical score increased are the yes/no connections. So if the user is feeling 'joy' and not 'frustration,' the score at the location where those two intersect increases. In the first training session, I found that I got way more data stored on the matrix, and this makes a little sense. Rather than trying to infer emotional connections, I'll be throwing away the connections that don't make any sense together. It's true that before any extensive input, it will look like most emotions WILL be connected, but that's beyond the point. I'd rather expose new connections that I've never thought of before rather than explaining the ones I made already and recalling those. This makes the clustering formula easier to apply as well; I hope to have the code for that done by the end of my winter break.