Unstructured Audio Classification for Environment Recognition

Abstract

My thesis aims to contribute towards building autonomous agents that are able to understand their surrounding environment through the use of both audio and visual information. To capture a more complete description of a scene, the fusion of audio and visual information can be advantageous in enhancing the system’s context awareness. The goal of this work is on the characterization of unstructured environmental sounds for understanding and predicting the context surrounding of an agent. Most research on audio recognition has focused primarily on speech and music. Less attention has been paid to the challenges and opportunities for using audio to characterize unstructured environments. Unlike speech and music, which have formantic structures and harmonic structures,