IEEE Transactions on Multimedia · 2008 · 14 citations · 21 references
EngineeringSpeech-language PathologyPredictive AnalyticsQuality EngineeringStatistical ModelingCommunication SystemsSpeech ImpairmentDegradationEquipment Degradation ModelingQuality DegradationQuality Degradation ModelingReference Model DesignReference Model GenerationService Quality DegradationSymbolic Regression
This paper proposes a novel approach to quantifying the quality degradation of Voice over IP (VoIP) telephony in the presence of codec and network-related impairments. This approach differs from the baisc ITU-T E-Model for VoIP quality estimation in that it addresses mixed narrowband/wideband scenarios. It makes novel use of instrumental models and symbolic regression via Genetic Programming (GP) to enable the evolution of degradation models from a modest set of initial parameters. Here, a two-step approach has been used. First, values of impairment factors are derived using WB-PESQ as a reference model. Secondly, a GP based symbolic regression approach has been utilized to automatically evolve the functional form of equipment impairment factors from a set of variables. Very few a priori assumptions are made about the model structure. The effectiveness of the approach is demonstrated by a number of generated models which compare favorably with WB-PESQ and outperform the traditional E-Model in terms of prediction accuracy when compared using WB-PESQ. A significant advantage of the approach is that new models are easily generated to account for continuing evolution of the VoIP standards.
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Michael O’Neill, Conor Ryan · IEEE Transactions on Evolutionary Computation · 2001 · 950 citations
Voice over IP performance monitoring
Robert Cole, J. H. Rosenbluth · ACM SIGCOMM Computer Communication Review · 2001 · 556 citations
Lexicographic parsimony pressure
Sean Luke, Liviu Panait · 2002 · 224 citations
Life Sciences, Evolutionary Biology, Evolutionary Theory +13