Scheirer E D
Machine Listening Group, MIT Media Laboratory, Cambridge, Massachusetts 02139, USA.
J Acoust Soc Am. 1998 Jan;103(1):588-601. doi: 10.1121/1.421129.
A method is presented for using a small number of bandpass filters and banks of parallel comb filters to analyze the tempo of, and extract the beat from, musical signals of arbitrary polyphonic complexity and containing arbitrary timbres. This analysis is performed causally, and can be used predictively to guess when beats will occur in the future. Results in a short validation experiment demonstrate that the performance of the algorithm is similar to the performance of human listeners in a variety of musical situations. Aspects of the algorithm are discussed in relation to previous high-level cognitive models of beat tracking.
本文提出了一种方法，该方法使用少量带通滤波器和并行梳状滤波器组来分析任意复音复杂度且包含任意音色的音乐信号的节奏，并从中提取节拍。这种分析是因果性的，并且可以用于预测未来节拍出现的时间。在一个简短的验证实验中的结果表明，该算法的性能在各种音乐情境下与人类听众的表现相似。本文还结合先前的节拍跟踪高级认知模型对该算法的各个方面进行了讨论。
