NOISE MITIGATION USING MACHINE LEARNING
    3.
    发明申请

    公开(公告)号:US20200043509A1

    公开(公告)日:2020-02-06

    申请号:US16598059

    申请日:2019-10-10

    Abstract: This disclosure relates to solutions for eliminating undesired audio artifacts, such as background noises, on an audio channel. A process for implementing the technology can include receiving a set of audio segments, analyzing the segments using a first ML model to identify a first probability of unwanted background noises in the segments, and if the first probability exceeds a threshold, analyzing the segments using a second ML model to determine a second probability that the one or more background features exist in the segments. In some aspects, the process can include attenuating audio artifacts in the segments, if the second probability exceeds a second threshold. In some implementations, dynamic time stretching and shrinking can be applied to the noise attenuation. Systems and machine-readable media are also provided.

    Predictive model for voice/video over IP calls

    公开(公告)号:US10091348B1

    公开(公告)日:2018-10-02

    申请号:US15659356

    申请日:2017-07-25

    Abstract: Disclosed is a system and method for forecasting the expected quality of a call. In some examples, a system or method can generate a plurality of scenarios from network metrics, retrieve historical ratings for the network metrics from users, and assign the historical ratings for the network metrics to the plurality of scenarios. The system or method can also filter one or more users based on similarities of the historical ratings for the plurality of scenarios with current network metrics, and forecast an expected call quality based on the historical ratings of the one or more filtered users.

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