A Music Similarity Function Based On Signal Analysis
A Music Similarity Function Based On Signal Analysis一种基于信号分析的音乐相似函数
We present a method to compare songs based solely on their audio content. Our technique forms a signature for each song based on K-means clustering of spectral features. The signatures can then be compared using the Earth Mover s Distance which allows comparison of histograms with disparate bins. Preliminary objective and subjective results on a database of over 8000 songs are encouraging. For 20 songs judged by two users, on average 2.5 out of the top 5 songs returned were judged similar. We also found that our measure is robust to simple corruption of the audio signal.
我们提供了一种方法，可以仅根据歌曲的音频内容来比较歌曲。我们的技术基于光谱特征的K-means聚类为每首歌形成一个签名。然后可以使用Earth Mover s Distance来比较这些签名，它允许将直方图与不同的箱子进行比较。对8000多首歌曲的初步客观和主观结果令人鼓舞。在由两名用户评判的20首歌曲中，排名前5的歌曲中平均有2.5首得到了相似的评价。我们还发现，我们的措施是稳健的简单破坏音频信号。
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