by Thilo Stadelmann et al
This is not mainstream research, but it is exactly what makes it interesting. The main idea of the paper is that to understand and develop speech algorithms we need to advance our tools to assist our intuition. This idea is quite fundamental and definitely has interesting extensions.
Modern tools are limited, most developers only check spectrograms and never visualize distributions, lattices or the context dependency trees. N-grams are also rarely visualized. In speech the paper suggests to build tools not just to view our models, but also to listen for them. I think this is quite a productive idea.
In modern machine learning tools visualization definitely helps to extend our understanding of complex structures. Here a terrific Colah's blog comes to mind. It would be interesting to extend this beyond pictures.