Acpas: a dataset of aligned classical piano audio and scores for audio-to-score transcription
semanticscholar(2021)
Abstract
We create the ACPAS dataset with aligned audio and scores on classical piano music for automatic music audioto-score transcription research. The dataset contains 497 distinct music scores aligned with 2189 audio performances, 179.8 hours in total. To our knowledge, it is currently the largest dataset for audio-to-score transcription research. We provide aligned performance audio, performance MIDI and MIDI scores, together with beat, key signature, and time signature annotations. The dataset is partly collected from a list of existing automatic music transcription (AMT) datasets, and partly synthesized. Both real recordings and synthetic recordings are included. We provide a train/validation/test split with no piece overlap and in line with splits in other AMT datasets.
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