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Real-time detection of musical onsets with linear prediction and sinusoidal modeling

机译:通过线性预测和正弦建模实时检测音乐发作

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Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This article provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets.
机译:实时音符开始检测在许多音频分析过程中起着至关重要的作用,例如乐谱跟随,节拍检测和各种分析方法进行的声音合成。本文提供了一些最常用的实时发作检测技术。我们提出了通过合并线性预测以及提出一种使用正弦建模进行实时发作检测的新算法来改善这些技术的方法。我们使用Modal(我们用于音乐起病检测的新开源库)评估了所有上述技术的检测准确性和计算性能,提供了全面的结果,该数据库提供了带有手标记音符起病样品的免费数据库。

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