Validating a real-time perceptual model predicting distraction caused by audio-on-audio interference

This work concentrates on validating a real-time perceptual model predicting distraction caused by audio-on-audio interference. The real-time model was recently developed on the basis of another successfully validated, perceptual distraction model, which is not able to calculate predictions in real time. Both models are non-blind, i.e., their inputs take target and interferer signals separately. This paper describes a validation experiment for the real-time distraction model, which compares the model's predictions to subjective distraction ratings obtained from a listening experiment. The accuracy of the real-time model is also compared to that of the original distraction model. The calculated root-mean-squared errors for a speech zone and a music zone were 10.2% and 12.6% for the real-time model, respectively, compared to 11.3% and 11.5% for the original model. The results indicate that the real-time model is able to predict the distraction with similar accuracy as the original model, and thus, is a suitable tool for sound-zone evaluation. Furthermore, the real-time capability of the model is considered to be vital for certain applications, including the evaluation of adaptive sound zones.