ge. We have contributed some research at the intersection of deep learning and audio, and presented our results. The most interesting results occur with a filter-based <em>activation maximization</em> function built from the gradients obtained from an input and its loss. Future work consists of (1) adapting DreamSound to intake different length YAMNet layers, as well as other models. (2) Further explorations with an adversarial model such as Kwgan is expected.<a href="#fn8" class="footnote-ref" id="fnref8" 