Abstract—Audio-visual services are now commonly used on the Internet. Many are based on batch downloading of contents for later replay, but real-time interactive and streaming services are rapidly becoming popular. Real-time services would benefit from quality of service if it were widely provided. The purpose with this paper is to show how QoS solutions may be introduced incrementally. The quality is obtained by means of a probe-based admission control that can be exerted outside the network. The introduction of the QoS starts from self-admission control in the application layer, followed by transport layer service differentiation. These two steps do not require any change to the network. If motivated, scheduling for service-class separation in the network may be added. We show by proof of concept how quality of service may be provided in agreement with the end-toend argument. The three steps of our proposal are compared and discussed with respect to the possibility of deployment.

In mobile speech communication, adverse conditions, such as noisy acoustic environments and unreliable network connections, may severely degrade the intelligibility and naturalness of the received speech quality, and increase the listening effort. This thesis focuses on countermeasures based on statistical signal processing techniques. The main body of the thesis consists of three research articles, targeting two specific problems: speech enhancement for noise reduction and flexible source coder design for unreliable networks. Papers A and B consider speech enhancement for noise reduction. New schemes based on an extension to the auto-regressive (AR) hidden Markov model (HMM) for speech and noise are proposed. Stochastic models for speech and noise gains (excitation variance from an AR model) are integrated into the HMM framework in order to improve the modeling of energy variation. The extended model is referred to as a stochastic-gain hidden Markov model (SG-HMM). The speech gain describes the energy variations of the speech phones, typically due to differences in pronunciation and/or different vocalizations of individual speakers. The noise gain improves the tracking of the time-varying energy of