A Kalman filter approach to packet loss replacement in presence of additive noise

A major problem in real-time packet-based communication systems, is misrouted or delayed packet which results in degraded perceived voice quality. If packets are not available on time, the packets are considered lost. The easiest solution in a network terminal receiver is to replace silence for the duration of lost speech segments. In a high quality communication system, to avoid degradation in speech quality due to packet loss, a suitable method or algorithm is needed to replace the missing segments of speech. In this paper, we introduce an adaptive filter for replacement of lost speech segment. In this method Kalman filter as a state-space based method will be used to predict the clean speech signal in presence of additive noise. The evaluation results show that Kalman filter has lower MSE compared to other methods in presence of White Gaussian Noise and background noise.