论文标题
POP2PIANO：基于流行音频的钢琴盖一代
Pop2Piano : Pop Audio-based Piano Cover Generation
论文作者
论文摘要
许多人都喜欢流行音乐的钢琴封面。但是，仍然研究了自动生成流行音乐的钢琴盖的任务。这部分是由于缺乏同步{POP，PIANO COVER}数据对，这使得应用最新的基于数据密集的深度学习方法变得具有挑战性。为了利用数据驱动方法的功能，我们使用自动管道进行大量配对和同步{POP，钢琴盖}数据。在本文中，我们提出了Pop2Piano，这是一个变压器网络，生成钢琴覆盖的流行音乐波形。据我们所知，这是第一个直接从流行音频生成钢琴盖的模型，而无需使用旋律和和弦提取模块。我们表明，经过数据集训练的Pop2piano能够制作出合理的钢琴盖。
Piano covers of pop music are enjoyed by many people. However, the task of automatically generating piano covers of pop music is still understudied. This is partly due to the lack of synchronized {Pop, Piano Cover} data pairs, which made it challenging to apply the latest data-intensive deep learning-based methods. To leverage the power of the data-driven approach, we make a large amount of paired and synchronized {Pop, Piano Cover} data using an automated pipeline. In this paper, we present Pop2Piano, a Transformer network that generates piano covers given waveforms of pop music. To the best of our knowledge, this is the first model to generate a piano cover directly from pop audio without using melody and chord extraction modules. We show that Pop2Piano, trained with our dataset, is capable of producing plausible piano covers.
