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In this paper, the authors demonstrate how speech signal features can be used to detect and explain differences in human to human conversation tests. To this end, they compare the results of two conversational VoIP quality experiments designed to quantify the impact of network delay on perceived speech quality. Both studies followed the same procedures and used the same scenarios, but were conducted in two different labs. Their comparison shows that the two studies, despite having been executed correctly using the same test design, still can produce surprisingly different results regarding the users quality perception on a MOS scale. In this respect, speech signal features extracted from conversation recordings help identifying divergent participant behavior as plausible cause for such differences.
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