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  • Broschiertes Buch

IP networks carry data traffic very well but they are not designed to carry voice traffic. Therefore, several degradations affect the quality of Voice over Internet Protocol (VoIP) traffic. An active area of research is the measurement of the quality of VoIP applications objectively, accurately and non-intrusively. One of the main methods for measuring VoIP quality is the E-model standardised by the ITU-T. The E-model is an objective and non- intrusive method for measuring the speech quality, but it depends on subjective tests to calibrate its parameters which are known to be time-consuming,…mehr

Produktbeschreibung
IP networks carry data traffic very well but they are not designed to carry voice traffic. Therefore, several degradations affect the quality of Voice over Internet Protocol (VoIP) traffic. An active area of research is the measurement of the quality of VoIP applications objectively, accurately and non-intrusively. One of the main methods for measuring VoIP quality is the E-model standardised by the ITU-T. The E-model is an objective and non- intrusive method for measuring the speech quality, but it depends on subjective tests to calibrate its parameters which are known to be time-consuming, expensive and hard-to-conduct. Consequently the E- model is applicable to limited number of network conditions. Also, it is less accurate than the intrusive methods such as Perceptual Evaluation of Speech Quality (PESQ) because it does not consider the contents of the received signal. In this book several improvements for the E-model based on PESQ are introduced to improve the E- Model's accuracy and to extend it to new network conditions based on packet loss classification.
Autorenporträt
Mousa AL-Akhras received his BSc and MSc degrees in Computer Science from the University of Jordan in 2000 and 2003, respectively. He received his PhD degree from De Montfort University, UK, in 2007. He is an assistant professor in CIS Department at the University of Jordan. Research interests include Artificial Neural Networks and VoIP and others.