Abstract
Quantifying the quality of a video or audio transmission over the Internet is usually a hard task, as based on the statistical processing of the evaluations made by a panel of humans (the corresponding and standardized area is called subjective testing). In this paper we describe a methodology called Pseudo-Subjective Quality Assessment (PSQA), based on Random Neural Networks, which is able to perform this task automatically, accurately and efficiently. RNN had been chosen here because of their good performances over other possibilities; this is discussed in the paper. Some new insights on PSQA’s use and performance are also given. In particular we discuss new results concerning PSQA–based dynamic quality control, and conversational quality assessment.
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Rubino, G., Tirilly, P., Varela, M. (2006). Evaluating Users’ Satisfaction in Packet Networks Using Random Neural Networks. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_32
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DOI: https://doi.org/10.1007/11840817_32
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