Another one for the list.
So based on @weefuzzy’s feedback in the “other thread”, part of creating a training set would be to sum a bunch of dicts to create an aggregate dict.
So this use case would be having an arbitrary amount of buffer slices (delineated by fluid.buftranslientslice~) which need to be written somewhere, then summed together, before then being stacked up into a multi-channel dict.
This is easy enough to do with individual buffers for everything… if you know how many transients you will get. If I’m feeding it some training audio, it may contain any number of hits. So I guess stacking them end-to-end in a single buffer, but keeping track of them (either with fixed durations or if the buftransient~ objects ever start spitting out “transient offsets”, then variable durations too), then once that process is complete, summing all of those together into a single buffer.
I guess this would require three individual buffers? One to concat all the transients into, another to sum them to (or can this happen “in place”?), then finally the actual multi-channel buffer that they will be stacked into, to feed fluid.nmfmatch~.