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Non-linear processing in cochlear spaced sub-bands using artificial neural networks for multi-microphone adaptive speech enhancement

机译:使用人工神经网络的人工耳蜗间隔子带中的非线性处理,以实现多麦克风自适应语音增强

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A general class of single hidden-layered, linear-in-the-parameters feedforward Artificial Neural Networks is proposed for processing band-limited signals in a multi-microphone sub-band adaptive speech enhancement scheme. The sub-band spacing within the adaptive speech enhancement system is set according to a published cochlear function. Comparative results achieved in simulation experiments demonstrate that the proposed sub-band scheme is capable of significantly outperforming conventional linear processing based wide-band and sub-band noise cancellation methods, in the presence of non-linear interference.
机译:提出了一种通用的单隐层参数线性前馈人工神经网络,用于处理多麦克风子带自适应语音增强方案中的带限信号。自适应语音增强系统中的子带间隔是根据已发布的耳蜗函数设置的。在模拟实验中获得的比较结果表明,在存在非线性干扰的情况下,提出的子带方案能够显着优于传统的基于线性处理的宽带和子带噪声消除方法。

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