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Neural dual extended Kalman filtering: applications in speech enhancement and monaural blind signal separation

机译:神经双重扩展卡尔曼滤波:在语音增强和单声道盲信号分离中的应用

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摘要

The removal of noise from speech signals has applications ranging from speech enhancement for cellular communications, to front ends for speech recognition systems. A nonlinear time-domain method called dual extended Kalman filtering (DEKF) is presented for removing nonstationary and colored noise from speech. We further generalize the algorithm to perform the blind separation of two speech signals from a single recording.
机译:从语音信号中去除噪声的应用范围从蜂窝通信的语音增强到语音识别系统的前端。提出了一种非线性时域方法,称为双扩展卡尔曼滤波(DEKF),用于消除语音中的非平稳和有色噪声。我们进一步概括该算法,以从单个记录中执行两个语音信号的盲分离。

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