Speech enhancement using normalized cumulant-based adaptive algorithm for transient noise
Speech enhancement using normalized cumulant-based adaptive algorithm for transient noise
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DOI：
10.1109/iscas.2014.6865634
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发表时间：
2014-06
期刊：
影响因子：
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通讯作者：
N. Sasaoka;Kazumasa Ono;Y. Itoh
中科院分区：
文献类型：
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作者：
N. Sasaoka;Kazumasa Ono;Y. Itoh
语音增强已被提出来减少嘈杂语音中的噪声。然而，难以减少与物体的固有振动相关的窄带分量的瞬态噪声。为了解决这个问题，我们提出了基于线性预测器和四阶累积量自适应算法的语音增强。然而，所提出的自适应算法由于步长太大而出现发散。因此，本文提出了一种基于归一化四阶累积量的自适应算法。所提出的自适应算法保证了自适应算法的收敛性。
Speech enhancement has been proposed to reduce noise in noisy speech. However, it is difficult to reduce the transient noise with a narrow band component which is associated with a natural oscillation of the object. In order to solve the problem, we have proposed the speech enhancement based on a linear predictor with 4th order cumulant adaptive algorithm. However, the divergence of the proposed adaptive algorithm occurs due to too large step size. Thus, this paper proposes a normalized 4th order cumulant based adaptive algorithm. The convergence of the adaptive algorithm is guaranteed by the proposed adaptive algorithm.