Piano covers of pop music are widely enjoyed, but generating them from music is not a trivial task. It requires great
expertise with playing piano as well as knowing different characteristics and melodies of a song. With Pop2Piano you
can directly generate a cover from a song's audio waveform. It is the first model to directly generate a piano cover
from pop audio without melody and chord extraction modules.
Pop2Piano is an encoder-decoder Transformer model based on
T5
. The input audio
is transformed to its waveform and passed to the encoder, which transforms it to a latent representation. The decoder
uses these latent representations to generate token ids in an autoregressive way. Each token id corresponds to one of four
different token types: time, velocity, note and 'special'. The token ids are then decoded to their equivalent MIDI file.
Pop2Piano is an Encoder-Decoder based model like T5.
Pop2Piano can be used to generate midi-audio files for a given audio sequence.
Choosing different composers in
Pop2PianoForConditionalGeneration.generate()
can lead to variety of different results.
Setting the sampling rate to 44.1 kHz when loading the audio file can give good performance.
Though Pop2Piano was mainly trained on Korean Pop music, it also does pretty well on other Western Pop or Hip Hop songs.
Citation
BibTeX:
@misc{choi2023pop2piano,
title={Pop2Piano : Pop Audio-based Piano Cover Generation},
author={Jongho Choi and Kyogu Lee},
year={2023},
eprint={2211.00895},
archivePrefix={arXiv},
primaryClass={cs.SD}
}
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