MATLAB 中的节拍提取
我没有 MATLAB 经验，不幸的是我的项目是在 MATLAB 中进行的。
基本上，目标是将音乐源（最好是 mp3 格式，但 .wav 也可以）读入 MATLAB，然后应用低通滤波器，过滤除节拍之外的所有内容。然后它应该获取每个节拍发生的时间并将结果写入文本文件。
I have no experience in MATLAB and unfortunately my project is in MATLAB.
Basically the objective is to read a music source (preferably in mp3 format but .wav is also OK) into MATLAB and then apply a low pass filter in such a way that it filters everything except the beats. Then it should get the time at which each beat occurs and write the results to a text file.
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我认为使用 .wav 文件要容易得多，尽管 Matlab 很好地提供了用于此类操作的实用程序，但事实上它确实如此： 读取 .wav
实现低通滤波器的最简单方法是移动平均滤波器。
最简单的方法是循环数据并取每组 n 个值的平均值。我不确定截止频率到底如何取决于 n，但你可以尝试一下。
另外，我知道Octave有一个信号处理工具包，并且我认为Matlab有内置的滤波器功能：https://ccrma.stanford.edu/~jos/fp/Matlab_Filter_Implementation.html
第三种方法是执行 FFT 并以频率进行滤波领域。
一旦获得信号的低频部分，您就可以检查高于幅度阈值的样本，并输出在数据中找到这些样本的位置。
It's quite a bit easier to work with .wav files I think, although Matlab way well have utilities for such things, in fact it does: Reading .wav
The easiest way to implement a low pass filter is a moving average filter.
The simplest way to do this would be be to loop over the data and take an average of each group of n values. I'm not sure exactly how the cutoff frequency would depend on n, but you could experiment a bit.
Otherwise, I know that there is a signal processing toolkit for Octave and I think that Matlab has a built-in filter function: https://ccrma.stanford.edu/~jos/fp/Matlab_Filter_Implementation.html
A third way which is over the top, would be to perform an FFT and do the filtering in the frequency domain.
Once you have the low-frequency part of the signal you can check for samples that are above an amplitude threshold and output where in the data these were found.
在 google 上搜索关键字“beat extract matlab”30 秒，得到以下两个代码源：
30 seconds on google with the keywords "beat extraction matlab" yield the following two code sources:
在Matlab中，您可以使用最先进的多特征节拍跟踪算法，该算法的信息发布在这里：
JR Zapata、M. Davies 和 E. Gómez，“多功能节拍跟踪器”，IEEE/ACM 音频、语音和语言处理汇刊。 22(4)，第 816-825 页，2014 年。 http://dx.doi.org /10.1109/TASLP.2014.2305252
多功能节拍跟踪器的 Matlab 实现是：
https://github.com/JoseRZapata/MultiFeatureBeatTracking
In Matlab you can use and state of the art Multi Feature beat tracker algorithm, the information of the algorithm is publish here:
J.R. Zapata, M. Davies and E. Gómez, "Multi-feature beat tracker," IEEE/ACM Transactions on Audio, Speech and Language Processing. 22(4), pp. 816-825, 2014. http://dx.doi.org/10.1109/TASLP.2014.2305252
The Matlab implementation of the multifeature beat tracker is:
https://github.com/JoseRZapata/MultiFeatureBeatTracking