A speech spectrum distortion measure with interframe memory

We present a novel spectral distortion measure with interframe memory. The memory gives the possibility to take into account the dynamics of the time evolution of the speech spectrum, which has shown to have a significant importance on the perceived speech quality. Memory is introduced by linear filtering of the time evolution of the difference log spectrum. This facilitates smoothing of spectrum with an ability to track quick transitions. Our results point at a substantially improved performance when rapidly evolving spectrum errors are punished in the measure