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Recent years have witnessed a growing interest in research related to thedetection of piano pedals from audio signals in the music information retrievalcommunity. However, to our best knowledge, recent generative models forsymbolic music have rarely taken piano pedals into account. In this work, weemploy the transcription model proposed by Kong et al. to get pedal informationfrom the audio recordings of piano performance in the AILabs1k7 dataset, andthen modify the Compound Word Transformer proposed by Hsiao et al. to build aTransformer decoder that generates pedal-related tokens along with othermusical tokens. While the work is done by using inferred sustain pedalinformation as training data, the result shows hope for further improvement andthe importance of the involvement of sustain pedal in tasks of pianoperformance generations.

Learning To Generate Piano Music With Sustain Pedals