I would like a few suggestions on an idea that I have -
I am trying to make a musical instrument (percussion), whilst just having a PVC disc. I am hitting the disc in a variety of styles (in order to produce a variety of sounds correspondingly), just like the way the actual percussion instrument is hit. I am converting the mechanical vibrations on the PVC disc to an electrical signal using a transducer, performing an FFT analysis of the different strokes, and trying to identify the stroke which is hit. Using this technique, I could get an accuracy of only 80 percent. I would like it to be extremely accurate ( more than 95 percent recognition). I was using only frequency as the parameter used to distinguish the sounds.
Now, I am thinking that if I could use other parameters too in order to identify the stroke, I might be able to get the required accuracy. I am thinking of resorting to Machine Learning for this. I am kind of new to this and would like to know what I might need to know before I proceed with this idea.
Any help would be greatly appreciated.