Title: A_PSQA: PESQ-like non-intrusive tool for QoE prediction in VoIP services
Abstract: Perceived speech quality, or Quality of Experience (QoE), is the key criteria for evaluating VoIP service. Most of the existing solutions are intrusive, in a sense where they require both the original and the transmitted audio sequences. These solutions give good estimation of the QoE, but they cannot be used in real-time. In fact, Service Provider and Network Provider are highly interested on automatic QoE estimation tool (without intrusion) in order to monitor and control the perceived quality of their VoIP service. In this paper, we present a new perceived speech quality estimation tool, named ALICANTE <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> Pseudo Subjective Quality Assessment (A_PSQA) for two widely VoIP codecs, iLBC and Speex. A_PSQA is a non-intrusive method, which relies on Random Neural Network (RNN) approach to learn the nonlinear relation between network parameters and the perceived user QoE. Furthermore, to avoid costly and time-consuming subjective tests, we used a well-known intrusive method ITU-T's Perceptual Evaluation Quality (PESQ) to estimate the MOS. Obtained results show that A_PSQA is able to estimate the MOS like PESQ, while being non-intrusive. Besides, A_PSQA's results are compared with two non-intrusive (IQX and E-Model) methods, where A_PSQA shows the highest correlation with PESQ estimation than all others methods.
Publication Year: 2012
Publication Date: 2012-06-01
Language: en
Type: preprint
Indexed In: ['crossref']
Access and Citation
Cited By Count: 17
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