The emergence of heterogeneous networks and the rapid increase of Voice over IP (VoIP) applications provide important opportunities for the telecommunications market. These opportunities come at the price of increased complexity in the monitoring of the quality of service (QoS) and the need for adaptation of transmission systems to the changing environmental conditions. This thesis contains three papers concerned with quality assessment and enhancement of speech communication systems in adverse environments. In paper A, we introduce a low-complexity, non-intrusive algorithm for monitoring speech quality over the network. In the proposed algorithm, speech quality is predicted from a set of features that capture important structural information from the speech signal. Papers B and C describe improvements in the conventional pre- and post-processing speech enhancement techniques. In paper B, we demonstrate that the causal Kalman filter implementation is in conflict with the key properties in human perception and propose solutions to the problem. In paper C, we propose adaptation of the conventional postfilter parameters to changes in the noisy conditions. A perceptually motivated distortion measure is used in the optimization of postfilter parameters. Significant improvement over nonadaptive system is obtained. / QC 20100824