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Inferring the quality of streaming video applications is important for Internet service providers, but the fact that most video streams are encrypted makes it difficult to do so. We develop models that infer quality metrics (\ie, startup delay and resolution) for encrypted streaming video services. Our paper builds on previous work, but extends it in several ways. First, the models work in deployment settings where the video sessions and segments must be identified from a mix of traffic and the time precision of the collected traffic statistics is more coarse (\eg, due to aggregation). Second, we develop a single composite model that works for a range of different services (\ie, Netflix, YouTube, Amazon, and Twitch), as opposed to just a single service. Third, unlike many previous models, our models perform predictions at finer granularity (\eg, the precise startup delay instead of just detecting short versus long delays) allowing to …