Perception of Complex Sounds in Noisy Environments

ABSTRACT: The goal of this Small Business Innovative Research project is to model the ability of human listeners to detect and identify specific auditory targets within complex, real-world sound environments. Previous approaches, based on linear auditory models, have produced unsatisfactory results. Our novel approach simulates the nonlinear signal processing observed in auditory physiology, significantly extending the state of the art. By mimicking functionally important nonlinearities, we are simulating human perceptual capabilities that are relevant to predicting the detection and identification of auditory targets. During Phase I we demonstrated the feasibility of this approach. In Phase II, we plan to develop an advanced computer model for predicting the capabilities of human listeners. We will 1) prototype a computer program that includes a dynamical model of the human auditory system and a decision model for predicting human performance; 2) design a new experiment using the database of aircraft and ambient sounds currently being collected by AFRL; and 3) validate the predictions of our computer model against the detection and identification performance of human listeners. BENEFIT: The model of auditory detection and identification we will develop will have broad implications for military, aerospace and automotive technologies. The model will predict sound source detection and identification in military environments, and will provide predictions across a wide variety of background noise configurations. This project is targeted toward a specific military application being developed at AFRL. Additionally, this model may prove useful in military training simulators, which have traditionally relied primarily on visual information and cues. In addition, the development and fielding of an auditory detection model has implications for automotive technology areas, the FAA, the U.S. Department of the Interior and National Park Service, by providing the ability to accurately predict auditory detection of aircraft and automobiles across a wide variety of locations, including residential areas, parks, and commercial zones. More generally, a technology that can successfully recognize complex sound patterns in natural environments would have significant implications for almost every application, military and civilian, that processes sound. Existing systems would be improved, deployment in new environments would be enabled, and new applications would become possible. Consumer applications would include hearing technologies, speech technologies, and music applications.