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Blind source separation of mixed speech in a high reverberation environment

机译:高混响环境中混合语音的盲源分离

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Blind source separation (BSS) is a technique for estimating and separating individual source signals from a mixed signal using only information observed by each sensor. BSS is still being developed for mixed signals that are affected by reverberation. In this paper, we propose combining the BSS method that considers reverberation proposed by Duong et al. with the BSS method reported by Sawada et al., which does not consider reverberation, for the initial setting of the EM algorithm. This proposed method assumes the underdetermined case. In the experiment, we compare the proposed method with the conventional method reported by Duong et al. and that reported by Sawada et al., and demonstrate the effectiveness of the proposed method.
机译:盲源分离(BSS)是一种仅使用每个传感器观察到的信息从混合信号中估计和分离单个源信号的技术。 BSS仍在开发中,用于受混响影响的混合信号。在本文中,我们建议结合考虑Duong等人提出的混响的BSS方法。使用Sawada等人报告的BSS方法,该方法不考虑混响,用于EM算法的初始设置。所提出的方法假设情况未定。在实验中,我们将提出的方法与Duong等人报道的常规方法进行了比较。以及Sawada等人的报道,并证明了该方法的有效性。

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