Abstract
The songwriting duo of John Lennon and Paul McCartney, the two founding members of the Beatles, composed some of the most popular and memorable songs of the last century. Despite having authored songs under the joint credit agreement of Lennon-McCartney, it is well-documented that most of their songs or portions of songs were primarily written by exactly one of the two. Furthermore, the authorship of some Lennon-McCartney songs is in dispute, with the recollections of authorship based on previous interviews with Lennon and McCartney in conflict. For Lennon-McCartney songs of known and unknown authorship written and recorded over the period 1962-66, we extracted musical features from each song or song portion. These features consist of the occurrence of melodic notes, chords, melodic note pairs, chord change pairs, and four-note melody contours. We developed a prediction model based on variable screening followed by logistic regression with elastic net regularization. Out-of-sample classification accuracy for songs with known authorship was 76\%, with a $c$-statistic from an ROC analysis of 83.7\%. We applied our model to the prediction of songs and song portions with unknown or disputed authorship.
Abstract (translated)
披头士乐队的两位创始成员约翰·列侬和保罗·麦卡特尼的歌曲创作组合,创作了上个世纪最受欢迎和最令人难忘的歌曲。尽管根据Lennon McCartney的联合信贷协议创作了歌曲,但有充分的证据表明,他们的大部分歌曲或歌曲的一部分主要是由两人中的一人创作的。此外,一些列侬·麦卡特尼歌曲的作者身份也存在争议,根据之前对列侬和麦卡特尼的访谈,人们对作者身份的回忆也存在冲突。对于在1962-66年间创作和录制的已知和未知作者的列侬·麦卡特尼歌曲,我们从每首歌曲或歌曲部分中提取音乐特征。这些特征包括旋律音符、和弦、旋律音符对、和弦变换对和四音符旋律轮廓的出现。我们建立了一个基于变量筛选的预测模型,然后用弹性网络正则化进行逻辑回归。已知作者歌曲的样本分类准确率为76%,ROC分析的统计数据为83.7%。我们将我们的模型应用于对作者身份不明或有争议的歌曲和歌曲部分的预测。
URL
https://arxiv.org/abs/1906.05427