Exploiting Frequency, Periodicity and Harmonicity Using Advanced Time-Frequency Concentration Techniques for Multipitch Estimation of Choir and Symphony
Exploiting Frequency, Periodicity and Harmonicity Using Advanced Time-Frequency Concentration Techniques for Multipitch Estimation of Choir and Symphony
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利用先进的时频集中技术，利用频率、周期性和和声进行合唱团和交响乐的多音高估计
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发表时间：
2016
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通讯作者：
Yi
中科院分区：
文献类型：
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作者：
Li Su;Tsung;Yi
为了推进自动音乐转录的研究，重要的是要使数据集具有足够的多样性和复杂性，以支持创建和评估稳健的算法来处理现实世界中的复调音乐信号中出现的问题。在本文中，我们提出了新的数据集，并研究了合唱和交响乐中多基音估计(MPE)的信号处理算法，这些算法在AMT研究中很少考虑。我们观察到，这两种音乐的MPE具有挑战性，这不仅是因为复调数字很高，而且可能是因为多名歌手或音乐家齐声演唱或演奏的音符的音高不精确。为了提高基音估计的稳健性，实验表明，综合考虑频率、周期和谐波信息来测量基音的显著程度是有益的。fi。此外，我们还可以通过多个锥化方法和时频集中(ConceFT)变换等非线性时频检测技术来提高基音的局部化和稳定性。结果表明，无论是在现有的还是在新创建的数据集上，所提出的无监督MPE方法都优于最新的监督方法，即使不是更好的话。
To advance research on automatic music transcription (AMT), it is important to have labeled datasets with suf-ficient diversity and complexity that support the creation and evaluation of robust algorithms to deal with issues seen in real-world polyphonic music signals. In this paper, we propose new datasets and investigate signal processing algorithms for multipitch estimation (MPE) in choral and symphony music, which have been seldom considered in AMT research. We observe that MPE in these two types of music is challenging because of not only the high polyphony number, but also the possible imprecision in pitch for notes sung or played by multiple singers or musicians in unison. To improve the robustness of pitch estimation, experiments show that it is beneficial to measure pitch saliency by jointly considering frequency, periodicity and harmonicity information. Moreover, we can improve the localization and stability of pitch by the multi-taper methods and nonlinear time-frequency reas-signment techniques such as the Concentration of Time and Frequency (ConceFT) transform. We show that the proposed unsupervised methods to MPE compare favorably with, if not superior to, state-of-the-art supervised methods in various types of music signals from both existing and the newly created datasets.