I'd like to know how recordings of many various sounds can be analyzed to allow for visualizations in two dimensions. My idea would be to find two data features (e.g. using principal component analysis) that make every sound class (dog bark, baby cry, etc.) distinguishable from others. I'm struggling to understand what parameters to focus on and which method to use.
Thanks for every comment.