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Adaptive Temporal Modeling of Audio Features in the Context of Music Structure Segmentation

机译:音乐结构分割背景下的音频特征自适应时间建模

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This paper describes a method for automatically adapting the length of the temporal modeling applied to audio features in the context of music structure segmentation. By detecting regions of homogeneous acoustical content and abrupt changes in the audio feature sequence, we show that we can consequently adapt temporal modeling to capture both fast- and slow- varying structural information in the audio signal. Evaluation of the method shows that temporal modeling is consistently adapted to different musical contexts, allowing for robust music structure segmentation while gaining independence regarding parameter tuning.
机译:本文介绍了一种在音乐结构分割的背景下自动调整应用于音频特征的时间建模长度的方法。通过检测均匀的声学内容和音频特征序列中突然变化的区域,我们表明我们可以适应时间建模,以捕获音频信号中快速变化和缓慢变化的结构信息。该方法的评估表明,时间建模始终如一地适用于不同的音乐环境,从而实现了稳健的音乐结构分割,同时获得了关于参数调整的独立性。

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