QoS Estimation and Prediction of Input Modality in Degraded IP Networks

Abstract

This paper evaluates the impact of combined transcoding and packet loss degradation on speech as input for the interactive voice response service (IVR) and proposes a method for classification of user input according to speech quality. Careful optimization of a communication system and all of its segments need to be considered, as the quality of the user's experience is becoming a more prominent part of the overall acceptance and desirability of modern service. Within our research, emulation environment was developed and the behavior of IVR analyzed under different packet loss and transcoding conditions. A set of frequently-used vocoders was tested on its performance with an automatic speech recognition module under degraded conditions. Further, quality estimation classifier was proposed, based on the Gaussian mixture models to determine best user's input modality. Various train and test parameters were investigated to provide more detailed insight of input quality estimation for IVR service working under error prone conditions.