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Filipe dos Santos Neves

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Subject Methods for Quality Enhancement of Voice Communications Over Erasure Channels
Advisor Salviano F. S. P. Soares
Group Information Systems and Processing
Status PhD student
Starts 2009/09/01
Ends 2015/07/17
Country Portugal
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Personal page http://www.it.pt/?fneves

This thesis presents a research work carried out by the author in the context of the Quality of Experience (QoE) in error-prone voice communication systems. Relevant research problems are identified and so the motivation for the investigation herein presented is established, starting from the disturbances that contribute to the impairment of the intelligibility experienced by users. Then, a review of the most important techniques currently found in the literature to enhance voice quality in communication systems prone to tansmission errors and data loss is presented. Packet Loss Concealment (PLC), Quality of Service (QoS) and packet prioritisation are addressed for this purpose. In the context of voice quality enhancement it is necessary to assess how much effective an enhancing technique is. Thus, the most significant methods used for telephony voice quality evaluation are described, considering the human subjective factors. Subjective methods of voice quality evaluation are reviewed and the relevant terminology is established. Then, objective methods, that are suitable for computational implementation to compute a score of the voice quality as it would be scored by an average subject are also reviewed. The most widely accepted and standard ones are studied, most of them released by the International Telecommunication Union (ITU). Special emphasis is given to Perceptual Evaluation of Speech Quality (PESQ), that uses a reference input signal and to E-Model, that essentially uses the characteristic parameters to provide an estimate of the transmission quality, taking into account the entire communication pathway of an end-to-end telephony system. A practical model for voice quality evaluation was investigated and validated according to the ITU Telecommunication Standardisation Sector (ITU-T) Rec. P.564 requirements. The results show that such a model complies with the therein specified class 2 of accuracy. Two linear interpolation algorithms permitting to reconstruct lost samples of voice signals transmitted through erasure channels are investigated and proposed as means to enhance the voice quality. After defining the concept of dimension in the resolution of a problem, as well as the key parameters that condition such kind of problems, the maximum dimension discrete version of the Papoulis-Gerchberg algorithm and a minimum dimension algorithm are described and used to implement a method of voice signal reconstruction. The results permit to conclude that these algorithms are suitable to recover missing samples when erasures exhibit an interleaved geometry and consider the interleaving structure of the samples in the source as a strategy to put, a priori, the problem in a well-conditioning point by judiciously choosing the key parameters. This thesis also describes a research study concerning voice packet classification according to the importance each one has in the overall voice quality. It aims to give them different priorities and preferentially lose those of less importance in networks with the capability of implementing channels with different priorities. A classification algorithm based on a dynamic programming approach is proposed and mathematically formulated to define a packet prioritisation scheme for transmission over priority networks. The results show that, under random packet loss, prioritised signals are less distorted and have better Mean Opinion Score (MOS) than signals sent without any priority. A novel technique combining this method and the Papoulis-Gerchberg algorithm is proposed with the aim of exploring synergies in the reconstruction of voice signals. The results show a decrease in the number of the Papoulis-Gerchberg iterations as well as a decrease in the reconstruction error. Overall, this novel technique contributes to enhance the performance of the signal reconstruction when using the maximum and minimum dimension processes, which can find useful applications in enhancing the QoE in voice communications.


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PhD thesis