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轻量混合框架用于声学回声消除与抑制

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该研究提出一种用于声学回声消除(AEC)与抑制的轻量级混合框架,结合深度学习与自适应滤波。框架采用多输出神经网络,联合更新滤波器参数并进行后处理;引入可学习的归一化最小均方(NLMS)滤波器变体,包含可变步长与可变过渡因子。为保证训练稳定,研究采用约束递归训练策略,并对滤波器输出施加上界约束。目前报道仅涉及该框架的方法设计,未见实验结果或后续进展。

Generated from reports · updated 3 hr ago

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Oct 8, 2026
  1. arXiv · Audio and Speech
    一种用于声学回声消除与抑制的轻量级混合框架:基于约束递归训练

    该研究提出一个结合深度学习与自适应滤波的声学回声消除(AEC)与抑制混合框架,用多输出神经网络联合更新滤波器参数并做后处理。框架引入可学习的归一化最小均方(NLMS)滤波器变体,含可变步长与可变过渡因子,并采用约束递归训练策略及滤波器输出上界约束以保证训练稳定。

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