FFT和机器学习在大调和弦识别中的应用

Nolan Monnier, Darien Ghali, Sophie X. Liu
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引用次数: 0

摘要

这个项目的目的是使用快速傅里叶变换理论和一种叫做Treebagger的机器学习算法来处理和识别和弦。选择了C、D、G、a四个和弦。要想成功,该程序必须能够识别不同八度的和弦和音乐倒位。我们的目标是使用采样和频率分解等数字信号处理技术对音频文件进行预处理,以便输入并训练成机器学习算法。对于我们的应用,我们使用了MATLAB的机器学习工具Treebagger。
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FFT and Machine Learning Application on Major Chord Recognition
The purpose of this project was to use theory of Fast Fourier Transforms and a machine learning algorithm called Treebagger in order to process and recognize musical chords. Four musical chords were selected: C, D, G, and A. To be successful, the program should recognize chords in various octaves and musical inversions. Our goal is to use digital signal processing techniques such as sampling and frequency decomposition to preprocess audio files for input and train into the machine learning algorithms. For our application, we used MATLAB's machine learning tool Treebagger.
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