  Cover song generation stands out as a popular way of music making in the
music-creative community. In this study, we introduce Piano Cover Generation
(PiCoGen), a two-stage approach for automatic cover song generation that
transcribes the melody line and chord progression of a song given its audio
recording, and then uses the resulting lead sheet as the condition to generate
a piano cover in the symbolic domain. This approach is advantageous in that it
does not required paired data of covers and their original songs for training.
Compared to an existing approach that demands such paired data, our evaluation
shows that PiCoGen demonstrates competitive or even superior performance across
songs of different musical genres.
