Real-Time, Non-intrusive Evaluation of VoIP

Speech quality, as perceived by the users of Voice over Internet Protocol (VoIP) telephony, is critically important to the uptake of this service. VoIP quality can be degraded by network layer problems (delay, jitter, packet loss). This paper presents a method for real-time, non-intrusive speech quality estimation for VoIP that emulates the subjective listening quality measures based on Mean Opinion Scores (MOS). MOS provide the numerical indication of perceived quality of speech. We employ a Genetic Programming based symbolic regression approach to derive a speech quality estimation model. Our results compare favorably with the International Telecommunications Union-Telecommunication Standardization (ITU-T) PESQ algorithm which is the most widely accepted standard for speech quality estimation. Moreover, our model is suitable for real-time speech quality estimation of VoIP while PESQ is not. The performance of the proposed model was also compared to the new ITU-T recommendation P.563 for non-intrusive speech quality estimation and an improved performance was observed.