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Multiresolution alignment for multiple unsynchronized audio sequences using Sequential Monte Carlo samplers

机译:使用顺序蒙特卡洛采样器对多个不同步音频序列进行多分辨率对齐

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With proliferation of smart devices such as smart phones, it is common that an event is recorded by multiple individuals creating several audio and video perspectives. Such user generated content is mostly unorganized (not synchronized). In this work, we consider the problem of aligning of multiple unsynchronized audio sequences and propose a multiresolution alignment algorithm using Sequential Monte Carlo samplers in a course to fine structure. The proposed method is evaluated with a real-life dataset from Jiku Mobile Video Datasets and has proven to be competitive with the baseline fingerprinting based alignment methods, with the proper choice of parameters.
机译:随着诸如智能电话之类的智能设备的激增,通常由多个人记录事件,从而创建多个音频和视频透视图。此类用户生成的内容大多是无组织的(未同步)。在这项工作中,我们考虑了多个不同步音频序列对齐的问题,并在逐步完善结构的过程中提出了使用顺序蒙特卡洛采样器的多分辨率对齐算法。用来自Jiku Mobile Video Datasets的真实数据集对提出的方法进行了评估,事实证明,该方法与基于基线指纹识别的比对方法具有竞争优势,并且可以选择适当的参数。

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