Towards Structural Analysis of Audio Recordings in the Presence of Musical Variations
Towards Structural Analysis of Audio Recordings in the Presence of Musical Variations
复制标题
对存在音乐变奏的录音进行结构分析
DOI：
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发表时间：
2007
影响因子：
1.9
通讯作者：
F. Kurth
中科院分区：
文献类型：
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作者：
Meinard Müller;F. Kurth
录音结构分析的一个主要目标是自动提取重复结构，或者更一般地说，提取底层音乐的音乐形式。最近解决这个问题的方法对于音乐来说效果很好，其中重复在乐器和节奏上基本一致，就像流行音乐的典型情况一样。然而，对于其他类别的音乐（例如西方古典音乐），音乐上相似的音频片段可能会在参数（例如动态、音色、音符组的执行、转调、发音和速度进展）方面表现出显着的变化。在本文中，我们提出了一种稳健且高效的音频结构分析算法，即使在这些参数存在较大变化的情况下，也可以识别音乐上相似的片段。为了解释这种变化，我们的主要思想是同时纳入各个层面的不变性：我们设计一种新型统计特征来吸收微变化，引入增强的局部距离测量来解释局部变化，并描述一种可以应对全局变化的新结构提取策略。我们对古典和流行音乐的实验结果表明，即使存在显着的音乐变化，我们的算法也能成功执行。
One major goal of structural analysis of an audio recording is to automatically extract the repetitive structure or, more generally, the musical form of the underlying piece of music. Recent approaches to this problem work well for music, where the repetitions largely agree with respect to instrumentation and tempo, as is typically the case for popular music. For other classes of music such as Western classical music, however, musically similar audio segments may exhibit significant variations in parameters such as dynamics, timbre, execution of note groups, modulation, articulation, and tempo progression. In this paper, we propose a robust and efficient algorithm for audio structure analysis, which allows to identify musically similar segments even in the presence of large variations in these parameters. To account for such variations, our main idea is to incorporate invariance at various levels simultaneously: we design a new type of statistical features to absorb microvariations, introduce an enhanced local distance measure to account for local variations, and describe a new strategy for structure extraction that can cope with the global variations. Our experimental results with classical and popular music show that our algorithm performs successfully even in the presence of significant musical variations.