New models for perceived voice quality prediction and their applications in playout buffer optimization for VoIP networks

Abstract

Perceived voice quality is an important metric in VoIP applications. The quality is mainly affected by network impairments such as delay, jitter and packet loss. Playout buffer at the receiving side can be used to compensate for the effects of jitter based on a tradeoff between delay and loss. The main aim in this paper is to find an efficient perceived quality prediction method for perceptual optimization of playout buffer. The contributions of the paper are three-fold. First, we propose an efficient new method for predicting voice quality for buffer design/optimization. The method can also be used for voice quality monitoring and for QoS control. In the method, nonlinear regression models are derived for a variety of codecs (e.g. G.723.1/G.729/AMR/iLBC) with the aid of ITU PESQ and the E-model. Second, we propose the use of minimum overall impairment as a criterion for buffer optimization. This criterion is more efficient than using traditional maximum mean opinion score (MOS). Third, we show that the delay characteristics of voice over IP traffic is better characterized by a Weibull distribution than a Pareto or an exponential distribution. Based on the new voice quality prediction model, the Weibull delay distribution model and the minimum impairment criterion, we propose a perceptual optimization buffer algorithm. Preliminary results show that the proposed algorithm can achieve the optimum perceived voice quality compared with other algorithms under all network conditions considered.