HIERARCHICAL DECORRELATION OF MULTICHANNEL AUDIO
    1.
    发明申请
    HIERARCHICAL DECORRELATION OF MULTICHANNEL AUDIO 审中-公开
    多通道音频的分层装饰

    公开(公告)号:US20160293176A1

    公开(公告)日:2016-10-06

    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.

    Abstract translation: 提供了用于多声道音频的分层去相关的方法,系统和装置。 分层去相关算法被设计为适应输入信号的可能变化的特性,并且还保留原始信号的能量。 该算法是可逆的,因为如果需要,可以检索原始信号。 此外,所提出的算法将解相关过程分解为多个低复杂度步骤。 这些步骤的贡献通常是递减的,从而可以缩放算法的复杂性。

    HIERARCHICAL DECCORELATION OF MULTICHANNEL AUDIO
    2.
    发明申请
    HIERARCHICAL DECCORELATION OF MULTICHANNEL AUDIO 有权
    多通道音频的分层分解

    公开(公告)号:US20140112481A1

    公开(公告)日:2014-04-24

    申请号:US13655225

    申请日:2012-10-18

    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.

    Abstract translation: 提供了用于多声道音频的分层去相关的方法,系统和装置。 分层去相关算法被设计为适应输入信号的可能变化的特性,并且还保留原始信号的能量。 该算法是可逆的,因为如果需要,可以检索原始信号。 此外,所提出的算法将解相关过程分解为多个低复杂度步骤。 这些步骤的贡献通常是递减的,从而可以缩放算法的复杂性。

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