Modelling the impact of network features on speech quality in voice over IP

With Voice and Video over IP spreading to the new areas of mobile communications, the speech quality becomes a concern of high importance. Monitoring systems of various types are deployed massively in the infrastructure of all the providers. These systems provide the knowledge base for the providers to set the infrastructure of theirs properly and efficiently. However, this approach only allows the administrators to react on the situation that already exists with a certain delay. In this paper the possible approach for speech quality estimation using the network fingerprint, data preprocessing and neural networks is presented. The description of the designed system is followed by the experimental measurements that confirm the validity of the approach. This way, the paper attempts to further improve the currently known methods for speech quality estimation.