  Classic public switched telephone networks (PSTN) are often a black box for
VoIP network providers, as they have no access to performance indicators, such
as delay or packet loss. Only the degraded output speech signal can be used to
monitor the speech quality of these networks. However, the current
state-of-the-art speech quality models are not reliable enough to be used for
live monitoring. One of the reasons for this is that PSTN distortions can be
unique depending on the provider and country, which makes it difficult to train
a model that generalizes well for different PSTN networks. In this paper, we
present a new open-source PSTN speech quality test set with over 1000
crowdsourced real phone calls. Our proposed no-reference model outperforms the
full-reference POLQA and no-reference P.563 on the validation and test set.
Further, we analyzed the influence of file cropping on the perceived speech
quality and the influence of the number of ratings and training size on the
model accuracy.
