Urban Sound Classification for Assistive Robotics

Robotic systems currently process information about the world primarily with camera sensors. Sound is a rich source of information, and can be leveraged to design robotic system that can better understand the world around them. This project builds a machine learning system for identifying urban sounds and tests for suitability as a part of an assistive robotic system.

Intern: Julio Cupe

Mentor: Aurora Schmidt (REDD)