Conversational call quality evaluator

    公开(公告)号:US09876901B1

    公开(公告)日:2018-01-23

    申请号:US15261635

    申请日:2016-09-09

    Applicant: Google Inc.

    Abstract: Aspects of the disclosure simulate a conversation over a real-time communication system and a reference script shared between the communication devices serves as a basis for comparison against the received speech-recognized conversation. A method of evaluating call quality of a real-time communication system that includes at least two communication devices is disclosed that includes receiving a reference script, the reference script containing linguistic contents of an audio signal being sent to one of the communication devices; generating an evaluation transcript by applying speech recognition to the audio signal being received; comparing the reference script with the evaluation transcript; and generating a call quality metric of the real-time communication system based on the comparison. The call quality metric may also include a communication delay which may be evaluated by determining a duration of a speaking turn; determining a duration of a listening turn from the audio signal being received by one of the communication devices; and estimating a communication delay of the audio signal based on the duration of the speaking turn and the listening turn.

    Hierarchical decorrelation of multichannel audio

    公开(公告)号:US10141000B2

    公开(公告)日:2018-11-27

    申请号:US15182751

    申请日:2016-06-15

    Applicant: GOOGLE INC.

    Abstract: Provided are methods, systems, and apparatus for hierarchical decorrelation of multichannel audio. A hierarchical decorrelation algorithm is designed to adapt to possibly changing characteristics of an input signal, and also preserves the energy of the original signal. The algorithm is invertible in that the original signal can be retrieved if needed. Furthermore, the proposed algorithm decomposes the decorrelation process into multiple low-complexity steps. The contribution of these steps is generally in a decreasing order, and thus the complexity of the algorithm can be scaled.

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