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New dataset boosts AI for recognizing historical music scores

Researchers have introduced the MusiCorpus dataset, a collection of 1,309 pages of historical and handwritten music scores. This dataset is designed to advance Optical Music Recognition (OMR) by providing a large-scale, realistic sample for training and evaluating machine learning systems. It includes MusicXML transcriptions and symbol annotations, addressing a critical gap in available training data for OMR. AI

影响 Enables development of AI systems to digitize and make machine-readable vast archives of historical music.

排序理由 The cluster describes a new dataset for a specific AI research task (OMR). [lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    A Dataset for the Recognition of Historical and Handwritten Music Scores in Western Notation

    A large amount of musical heritage has been digitised by memory institutions: libraries, museums, and archives. Nevertheless, the field of Optical Music Recognition (OMR) has struggled with making this music machine-readable, despite advances in deep learning, mostly because no d…