Speech quality prediction for artificial bandwidth extension algorithms

During the transition period from narrowband to wideband speech transmission services, Artificial Bandwidth Extension (ABE) algorithms are able to reduce the perceptual degradation of narrowband-transmitted speech signals by extending the audio bandwidth. In this paper, we analyze whether the resulting speech quality can be predicted reliably with instrumental models. Estimations from the new ITU standard POLQA, its predecessor WB-PESQ and the diagnostic DIAL model are compared to subjective listener judgments. This comparison reveals that the instrumental measures are not fully able to cope with ABE-processed speech, particularly in predicting ABE rank orders reliably. Reasons for this finding and corresponding diagnoses are discussed.