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Robust underdetermined blind audio source separation of sparse signals in the time-frequency domain

机译:时频域中稀疏信号的鲁棒欠定盲音频源分离

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We address the problem of blind source separation in the underdetermined and instantaneous mixture case. The proposed method is based on an algorithm developed by Aissa-El-Bey and al.. This algorithm requires a good choice of the noise threshold and does not take into account the noise contribution in the inversion process. In order to overcome these drawbacks, this paper presents a robust underdetermined blind source separation approach. Robustness is achieved by estimating the noise standard deviation and using this estimate in the inversion process and the expression of the noise threshold. The good performance of the proposed method is shown by comparison with state-of-the-art methods.
机译:我们解决了未确定和瞬时混合箱中盲源分离的问题。该方法基于Aissa-El-Bey和Al开发的算法。该算法需要良好的噪声阈值选择,并且不会考虑反转过程中的噪声贡献。为了克服这些缺点,本文提出了一种坚固的未确定的盲源分离方法。通过估计噪声标准偏差并在反转过程中使用该估计和噪声阈值的表达来实现鲁棒性。通过与最先进的方法相比,示出了所提出的方法的良好性能。

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