Recently, the binaural auditory-model-based quality prediction (BAM-Q) was successfully applied to predict binaural audio quality degradations, while the generalized power-spectrum model for quality (GPSM$^\text{q}$) has been demonstrated to account for a large variety of monaural signal distortions. For many applications, a combined monaural and binaural model would be advantageous, however, the contribution of monaural and binaural quality aspects to overall (spatial) quality is not conclusively clarified. Thus, the current study systematically investigated overall audio quality in a listening experiment for monaural and binaural distortions on music, speech, and noise, applied either in isolation or in combination. The resulting database was used for assessing different methods for combining BAM-Q and GPSM$^\text{q}$to joint overall audio predictions for monaural and binaural signal distortions. It was investigated, if monaural or binaural quality aspects contribute stronger to overall audio quality. The results indicate that overall audio quality depends on the lower quality aspect, either monaural or binaural.

A perceptual, binaural audio-quality model is introduced. The model was developed for predicting any kinds of perceived spatial quality differences between two audio signals in multi-channel reproduction and audio processing schemes. It employs a recent binaural auditory model as front-end to provide perceptually relevant binaural features for the reference and test audio signal. Correlations between the binaural features of both signals are combined to an overall spatial quality measure by the use of multivariate adaptive regression splines (MARS). Furthermore, a database was generated to train and evaluate the model. The database contains various multi-channel audio signals, which were subjectively assessed in formal listening tests with 15 trained listeners. The results show different model prediction performances depending on the type of quality degradation. Combination of the proposed spatial quality measure with established monaural quality measures improved the predictive power.