Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique

Abstract

At the core of augmented reality audio (ARA) technology lies the ARA mix, a process responsible for the assignment of a virtual environment to a real one. Legacy ARA mix models have focused on the natural reproduction of the real environment, whereas the virtual environment is simply mixed through fixed gain methods. This study presents a novel approach of a dynamic ARA mix that facilitates a smooth adaptation of the virtual environment to the real one, as well as dynamic control of the virtual audio engine, by taking into account the inherent characteristics of both ARA technology and binaural auditory perception. A prototype feature extraction technique of auditory perception characteristics through a real-time binaural loudness prediction method was used to upgrade the legacy ARA mix model into a dynamic model, which was evaluated through benchmarks and subjective tests and showed encouraging results in terms of functionality and acceptance.