Wei Zeng

Piano performance MIDI-to-score transcription has treated notes as the only modeling unit, yet beats can fall on frames with no note onset, so metrical information struggles to reach the notation. DuET runs a note encoder and a frame-level encoder over notes and a fixed time grid, exchanges information through bidirectional cross-attention, and lets a decoder alternate between the two representations to predict durations, bars, staves and other score attributes. On the popular-piano Gangqinpu test split it lowers MUSTER mean error from 6.56% for the strongest baseline to 3.64%, and on the classical ASAP split from 11.30% to 11.22%.

Piano performance MIDI-to-score transcription has treated notes as the only modeling unit, yet beats can fall on frames with no note onset, so metrical information struggles to reach the notation. DuET runs a note encoder and a frame-level encoder over notes and a fixed time grid, exchanges information through bidirectional cross-attention, and lets a decoder alternate between the two representations to predict durations, bars, staves and other score attributes. On the popular-piano Gangqinpu test split it lowers MUSTER mean error from 6.56% for the strongest baseline to 3.64%, and on the classical ASAP split from 11.30% to 11.22%.