Various studies have shown that the instrumental measures wideband PESQ and POLQA are not reliably predicting speech quality for artificial speech bandwidth extension (ABE) test conditions, as this has never been their scope. Based on data from a coordinated subjective listening test with 12 ABE variants developed by 6 different institutions, conducted in 4 languages, we propose in this work a novel instrumental quality measure that is specifically suited for narrowband-to-wideband ABE test conditions. In particular, our contributions are fourfold: First, we propose quality indicators particularly being able to detect ABE-related distortions. Second, we investigate the combination of perceptually and nonperceptually motivated distortion-related statistics. Third, we propose a support-vector-machine-based high-performance MOS predictor for ABE speech quality assessment, finally, we present the training process based on the subjective listening test data. A k-fold cross-validation test on 1) disjoint languages, 2) disjoint speakers, and 3) disjoint ABE solutions proves the superiority of our proposed measure in the ITU-T-recommended categories accuracy, consistency, and linearity compared to both, wideband PESQ and POLQA.
