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The authors analyzed 70 voice traces collected from IP-telephony applications, multicast lectures, and multimedia conferencing sessions which involve multiple speakers and different dynamics of interaction beyond two-way conversations. Results show that application differences have significant impact on the traffic characteristics. The conventional exponential model, established for telephone conversations, fails to accurately capture the packet level activity observed in these traces, e.g., the heavy-tail distributions of the talkspurt and silence periods. They classify the traces into four types based on their audio contents: audience, lecture, multi-party conferencing and conversation. Further analysis shows that Weibull is a better matching statistical model and achieves lower mean-square-error than the exponential model (By 1 to 2 orders of magnitude) in approximating the audio streams for all four cases.
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