Parametric Audio-visual Quality Measurement Based on Interpretable Fuzzy Logic

In this paper, a fuzzy inference based system for the quality of experience assessment is presented. In particular, two models have been proposed to assess the perceived quality of experience. The first one is a global model which estimates the overall audiovisual quality without going through the individual evaluations of visual and auditory modalities while the other model has been created by merging fuzzy inference systems based on separate auditory and visual objective quality scores. Two different sets of parameters have been tested for the second model leading to two different measures. The contribution of this research lies in the application of the fuzzy inference logic to estimate the audiovisual quality of multimedia data. The experimental results on a publicly available quality dataset show competitive predictive performances of the proposed measures when compared to two existing audiovisual metrics based on random forests regression and multilayer perceptron.