A Metric for Predicting the Quality of Ambisonic Spatial Audio Reproduced Using Spatially Interpolated or Extrapolated Room Impulse Responses

Abstract

In virtual reality (VR), sound sources are convolved with room impulse responses (RIRs) to create immersive and dynamic audio experiences. Assessing the quality of spatial audio synthesis in VR is challenging. Subjective listening tests are accurate, but they are time-consuming and costly. This paper introduces a novel objective quality metric to predict the listening quality (LQ) and localization accuracy (LA) of Ambisonic spatial audio at new positions using spatially interpolated or extrapolated first-order Ambisonic (FOA) RIRs based on known nearby FOA RIRs. The LQ and LA scores are computed based on the Kolmogorov-Smirnov test, to measure the similarity between segments of direct sound and reflections of reference and synthesized FOA RIRs. Results show that these scores strongly correlate with subjective test results, proving the reliability of the proposed method. A major advantage is that it predicts spatial audio quality directly from synthesized FOA RIRs, without requiring convolved signals or being affected by specific sound sources, providing a more practical and efficient solution for development.