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A Novel Fuzzy-Based Automatic Speaker Clustering Algorithm

机译:一种基于模糊的新型说话人自动聚类算法

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Fuzzy clustering has been proved successful in various fields in the recent past. In this paper, we introduce fuzzy clustering algorithms into the domain of automatic speaker clustering, and present a novel fuzzy-based hierarchical speaker clustering algorithm by applying fuzzy theory into the state-of-the-art agglomerative hierarchical clustering. This method follows a bottom-up strategy, and determines the fuzzy memberships according to a membership propagation strategy, which propagates fuzzy memberships in the iterative process of hierarchical clustering. Further analysis reveals that this method is an extension of conventional hierarchical clustering algorithm. Experiment results show that our method exhibits quite competitive performances compared to conventional k-means, fuzzy c-means and agglomerative hierarchical clustering algorithms.
机译:最近,模糊聚类在各个领域都被证明是成功的。在本文中,我们将模糊聚类算法引入自动说话者聚类领域,并通过将模糊理论应用于最新的聚集聚类聚类中,提出一种新颖的基于模糊的层次说话者聚类算法。该方法遵循自下而上的策略,并根据成员资格传播策略确定模糊成员资格,从而在层次聚类的迭代过程中传播模糊成员资格。进一步的分析表明,该方法是对传统层次聚类算法的扩展。实验结果表明,与传统的k均值,模糊c均值和聚类的聚类聚类算法相比,我们的方法具有很好的竞争性能。

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