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    PREDICTING MULTIMEDIA SESSION MOS
    2.
    发明公开
    PREDICTING MULTIMEDIA SESSION MOS 审中-公开

    公开(公告)号：EP3420698A1

    公开(公告)日：2019-01-02

    申请号：EP17708715.2

    申请日：2017-02-22

    申请人： Telefonaktiebolaget LM Ericsson (PUBL)

    发明人： FU, Jing ,  SHAIKH, Junaid ,  LUNDBERG, Tomas ,  HEIKKILÄ, Gunnar

    IPC分类号： H04L29/06 ,  H04N21/24 ,  H04N21/442

    摘要： It is provided a method, performed by a MOS, Mean Opinion Score, estimator, for predicting a multimedia session MOS. The multimedia comprises a video and an audio, wherein video quality is represented by a list of per time unit scores of a video quality, an initial buffering event and rebuffering events in the video, and wherein audio quality is represented by a list of per time unit scores of audio quality. The method comprises: generating video features from the list of per time unit scores of the video quality; generating audio features from the list of per time unit scores of the audio quality; generating buffering features from the initial buffering event and rebuffering events in the video; and estimating a multimedia session MOS from the generated video features, generated audio features and generated buffering features by using machine learning technique.

    PREDICTING MULTIMEDIA SESSION MOS
    8.
    发明公开
    PREDICTING MULTIMEDIA SESSION MOS 审中-公开

    公开(公告)号：EP3806418A1

    公开(公告)日：2021-04-14

    申请号：EP20196621.5

    申请日：2017-02-22

    申请人： Telefonaktiebolaget LM Ericsson (publ)

    发明人： FU, Jing ,  SHAIKH, Junaid ,  Lundberg, Tomas ,  Heikkilä, Gunnar

    IPC分类号： H04L29/06 ,  H04N21/24 ,  H04N21/442 ,  H04N21/439

    摘要： It is provided a method, performed by a MOS, Mean Opinion Score, estimator, for predicting a multimedia session MOS. The multimedia comprises a video and an audio, wherein video quality is represented by a list of per time unit scores of a video quality, an initial buffering event and rebuffering events in the video, and wherein audio quality is represented by a list of per time unit scores of audio quality. The method comprises: generating video features from the list of per time unit scores of the video quality; generating audio features from the list of per time unit scores of the audio quality; generating buffering features from the initial buffering event and rebuffering events in the video; and estimating a multimedia session MOS from the generated video features, generated audio features and generated buffering features by using machine learning technique.