Multiple-F0 estimation of piano sounds exploiting spectral structure and temporal evolution

Multiple-F0 estimation of piano sounds exploiting spectral structure and temporal evolution
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利用频谱结构和时间演化对钢琴声音进行多 F0 估计

DOI:
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发表时间:
2010
期刊:
SAPA@INTERSPEECH
影响因子:
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通讯作者:
S. Dixon
S. Dixon
中科院分区:
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文献类型:
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作者:
Emmanouil Benetos;S. Dixon

文献摘要

被引文献

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本文提出了一个系统的多个基本频率估计的钢琴声使用音高候选选择规则,采用频谱结构和时间演变。作为一个时间-频率表示,谐振器时频图像的输入信号,使用的噪声抑制模型,并进行频谱白化过程。此外,还采用基于谱通量的起始检测器来选择所产生声音的稳态区域。在多F0估计阶段,调谐和非谐性参数被提取,并提出了一个音高显著性函数。音高存在性测试利用来自音高候选者的频谱结构的信息来执行,旨在抑制在真实音高的倍数和约数处发生的误差。提出了一种新的特征,用于谐波相关的音高的估计,基于共同的幅度调制假设。实验进行的MAPS数据库上使用8784钢琴样本的古典,爵士乐,和随机和弦与复调水平之间的1和6。所提出的系统是计算成本低廉,能够执行多个F0估计实验的实时。实验结果表明,该系统优于国家的最先进的方法,上述任务在统计上显着的方式。
This paper proposes a system for multiple fundamental frequency estimation of piano sounds using pitch candidate selection rules which employ spectral structure and temporal evolution. As a time-frequency representation, the Resonator TimeFrequency Image of the input signal is employed, a noise suppression model is used, and a spectral whitening procedure is performed. In addition, a spectral flux-based onset detector is employed in order to select the steady-state region of the produced sound. In the multiple-F0 estimation stage, tuning and inharmonicity parameters are extracted and a pitch salience function is proposed. Pitch presence tests are performed utilizing information from the spectral structure of pitch candidates, aiming to suppress errors occurring at multiples and sub-multiples of the true pitches. A novel feature for the estimation of harmonically related pitches is proposed, based on the common amplitude modulation assumption. Experiments are performed on the MAPS database using 8784 piano samples of classical, jazz, and random chords with polyphony levels between 1 and 6. The proposed system is computationally inexpensive, being able to perform multiple-F0 estimation experiments in realtime. Experimental results indicate that the proposed system outperforms state-of-the-art approaches for the aforementioned task in a statistically significant manner.