In this thesis I present explorative work that shows how sounds beyond speak can be used on the input side in the design of interactive experiences and natural interfaces. By engaging in explorative approaches with a material view on sound and interactive machine learning, I’ve shown how these two counterparts may be combined with a goal to envision new possibilities and perspectives on sonic natural interfaces beyond speech. This exploration has been guided with a theoretical background of design materials, machine learning, sonic interaction design and with a research through design driven process, I’ve used iterative prototyping and workshops with participants to conduct knowledge and guide the explorative process. My design work has resulted in new prototyping tools for designers to work with sound and interactive machine learning as well as a prototypes concept for kids that aims to manifest the material ndings around sound and interactive machine learning that I’ve done in this project. By evaluating my design work in contextual settings with participants, I’ve conducted both analytical and productive investigations than can construct new perspectives on how sound based interfaces beyond speech can be designed to support new interactive experiences with artefacts. Here my focus has been to engage with sound as a design material from both contextual and individual perspectives, and how this can be explored by end-users empowered by interactive machine learning to foster new forms of creative engagement with our physical world.