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Adaptive microphone array-based filter in the speech enhancement

机译:语音增强中的自适应麦克风阵列基于滤波器

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This study applied microphone array technology to develop an adaptive hybrid filter for enhancing speech signals. In the past decade, numerous studies have confirmed the excellent performance of microphone array technology in speech source localization and noise reduction. The proposed hybrid filter applies adaptive wavelet filter and spectral subtraction method for signal processing before filtering the signals by microphone array. Both the spectral subtraction method and adaptive wavelet thresholding method are highly effective for signal denoising. However, spectral subtraction method is ineffective for low-SNR signals whereas adaptive wavelet thresholding method is ineffective for high-frequency signals. The filtering behavior between adaptive wavelet filter and spectral subtraction method is controlled by a feedforward fuzzy neural network. Experimental results reveal that the proposed filter outperforms other methods of speech signal enhancement.
机译:本研究应用了麦克风阵列技术来开发用于增强语音信号的自适应混合滤波器。 在过去的十年中,众多研究已经证实了麦克风阵列技术在语音源定位和降噪中的优异性能。 所提出的混合滤波器应用自适应小波滤波器和光谱减法方法,用于通过麦克风阵列过滤信号之前的信号处理。 频谱减法方法和自适应小波阈值阈值方法都非常有效地用于信号去噪。 然而,光谱减法方法对于低SNR信号是无效的,而自适应小波阈值方法对于高频信号无效。 自适应小波滤波器和光谱减法方法之间的过滤行为由前馈模糊神经网络控制。 实验结果表明,所提出的滤波器优于其他语音信号增强方法。

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