  Recent years have witnessed a growing interest in research related to the
detection of piano pedals from audio signals in the music information retrieval
community. However, to our best knowledge, recent generative models for
symbolic music have rarely taken piano pedals into account. In this work, we
employ the transcription model proposed by Kong et al. to get pedal information
from the audio recordings of piano performance in the AILabs1k7 dataset, and
then modify the Compound Word Transformer proposed by Hsiao et al. to build a
Transformer decoder that generates pedal-related tokens along with other
musical tokens. While the work is done by using inferred sustain pedal
information as training data, the result shows hope for further improvement and
the importance of the involvement of sustain pedal in tasks of piano
performance generations.
