A neural network based model for VoIP speech quality prediction
Jiuchun Ren, Dilin Mao, Zhiwei Wang · 2009
It is increasingly important to model the VoIP speech quality. Network factors (e.g packet loss) and source impairments (e.g. codec type) should be considered in any proposed solution. Some new factors's affection, such as jitter standard deviation, is recently studied. In this paper, we proposes a new neural network models for predicting VoIP speech quality. The proposed approach use intrusive methods (PESQ) for neural network training, which avoids time-consuming subjective tests.