Abstract
The growth of Internet has led to the development of many new applications and technologies. Voice over Internet Protocol (VoIP) is one of the fastest growing applications. Calculating the quality of calls has been a complex task. The ITU E-Model gives a framework to measure quality of VoIP calls but the MOS element is a subjective measure. In this paper, we discuss a novel method using Random Neural Network (RNN) to accurately predict the perceived quality of voice and more importantly to perform this on real-time traffic to overcome the drawbacks of available methods. The novelty of this model is that RNN model provides a non-intrusive method to accurately predict and monitor perceived voice quality for both listening and conversational voice. This method has learning capabilities and this makes it possible for it to adapt to any network changes without human interference.
Original language | English |
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Title of host publication | Proceedings of the 9th International Conference on Networks (ICN) 2010 |
Publisher | IEEE |
ISBN (Print) | 9780769539799 |
DOIs | |
Publication status | Published - 1 Jan 2010 |
Event | Ninth International Conference on Networks - Hôtel Latitudes Les Bruyeres, Les Menuires, France Duration: 11 Apr 2010 → 16 Apr 2010 https://www.iaria.org/conferences2010/ICN10.html (Link to conference website) |
Conference
Conference | Ninth International Conference on Networks |
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Abbreviated title | ICN 2010 |
Country/Territory | France |
City | Les Menuires |
Period | 11/04/10 → 16/04/10 |
Internet address |
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Keywords
- communications technology
- voice quality
- random neural networks
- engineering