Yeah.
Um ,  so , uh , the big picture is k um ,  come up with a set of ,  uh , intermediate categories , then build intermediate category classifiers , then do recognition , and , um , improve speech recognition in that way. Um , so right now I 'm in  in the phase where  I 'm looking at  at , um , deciding on a initial set of intermediate categories. And  I 'm looking  for data data - driven  methods that can help me find ,  um , a set of intermediate categories  of speech that , uh , will help me to discriminate  later down the line. And one of the ideas ,  um , that was to take a  take a neural net  train  train an ordinary neural net  to   uh , to learn the posterior probabilities of phones. And so , um , at the end of the day you have this neural net and it has hidden   hidden units. And each of these hidden units is   um , is learning some sort of pattern. And so , um , what  what are these patterns ?
Hmm.
I don't know. Um , and I 'm gonna to try to   to look at those patterns  to  to see ,  um ,  from those patterns  uh , presumably those are important patterns for discriminating between phone classes. And maybe   maybe some , uh , intermediate categories can come from  just looking at the patterns of   um , that the neural net learns.