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

Abstract

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.

On the Influence of Transfer Function Noise on Sound Zone Control in a Room

“…With Bayesian inference it is possible to estimate the transfer functions and express the certainty of the estimate given the observed data. Throughout the appendix, the signal model from (10) - (14) is used, while the subscript (•) m and the frequency dependence (f n ) are ommitted for the ease of notation. The procedure for determining the marginal distribution for the transfer function is summarized in the end of the appendix.…”

“…Reproducing individual audio for two listeners (content A and B) is achieved by superimposing two sound zones solutions, where the bright zone with respect to audio content A is the dark zone with respect to content B and vice versa. Perceptual studies indicate that 25 to 29 dB loudness difference 1 between the target and interfering audio is sufficient for not being distracted by the interfering audio [14].…”

“…Jesper Kjaer Nielsen (S'12-M'13) received the M.Sc (Cum Laude) and Ph.D. degrees in electrical engineering with a specialisation in signal processing from Aalborg University, Denmark, in 2009 and 2012, respectively. From 2012 to 2016, he was with the Department of Electronic Systems, Aalborg University, as an industrial postdoctoral researcher (12)(13)(14)(15) and as a non-tenured associate professor (15)(16). Bang & Olufsen A/S (B&O) was the industrial partner in these four years.…”

Isolation performance metrics for personal sound zone reproduction systems

“…Over the past two decades, various PSZ reproduction systems have been implemented with different loudspeaker configurations and sound zone specifications depending on the application scenario. The loudspeakers used in a PSZ system have been configured as linear [2][3][4][5] , circular [6][7][8][9][10][11] , arc-shaped 12,13 arrays in the far field, or in the near field (e.g., headrest loudspeakers in automotive cabins 14,15 ).The sound zones have been designed to be as large as a few meters 2,3,[6][7][8][9] , or as small as a region that only includes the listeners' heads or ears 4,5,7,10,[12][13][14][15] .…”

“…As will be shown, it does not reflect the isolation performance of other rendering modes, where multichannel programs with different inter-channel correlations (e.g., stereo and binaural programs 17 ) are specified as input. In addition, while AC represents the isolation between sound zones, it does not give a measure of the level difference between programs in the same zone, which is more relevant to the the listener's perception of audio-on-audio interference 10,11,18 (excluding psychoacoustic masking effects).…”