Ethan Nevidomsky

Ethan  Nevidomsky
Advisor: Dorothy Curtis
Department: EECS
Areas of Research: CS+HASS
Years: 2021-2022
Research Project Title:

Using Machine Learning to Generate Spatial Audio Experiences

abstract:Spatial audio is becoming more mainstream through its support by more software and hardware technologies, including speaker systems, headphones, stores, and streaming services. Despite increasing hardware support, the software needed to make spatial audio experiences is still developing, and many audio experiences could take advantage of new strides in hardware if spatializing them was easier. I plan to investigate ways in which machine learning and other techniques can help serve as a creative tool in the spatial audio experience, both in generating new audio soundscapes and adapting existing recordings to a spatial experience. A possible final goal would be to create a novel ML model that will be easy for artists to use to enhance their ability to create spatialized audio experiments.

I am participating in SuperUROP because I have been looking for ways to make an impact at the intersection of art and technology, and I believe doing research in a lab that brings in artists is the best way to understand and impact the field. I hope to see what research at this boundary looks like and spending a whole year on exploring and developing possibilities should allow me to create a finished toolkit which is actually useful in the end.