In streaming applications, unequal protection of audio and video tracks may be necessary to maintain the optimal perceived overall quality. For this purpose, the application should be aware of the relative importance of audio and video in an audiovisual sequence. In this paper, we propose a subjective test arrangement for finding the optimal tradeoff between subjective audio and video qualities in situations when it is not possible to have perfect quality for both modalities concurrently. Our results show that content poses a significant impact on the preferred compromise between audio and video quality, but also that the currently used classification criteria for content are not sufficient to predict the users' preference.
This paper proposes a methodology for the development of a computational quality model for IP-based audio. The project mainly focuses on two questions: 1) choice of a quality measurement scale in the computational model and mapping of this scale with existing audio quality measurement metrics, and 2) quantification of encoding and packet loss impairments (only two quality degradation parameters are considered; others will be discussed in future work). The objective PEAQ algorithm in the SEAQ software implementation is used for the parameter quantification and the model accuracy estimation.
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