MuScriptor: An Open Model for Multi-Instrument Music Transcription

Simon Rouard, Michael Krause, Axel Roebel, Carl-Johann Simon-Gabriel, Alexandre Défossez

MuScriptor: An Open Model for Multi-Instrument Music Transcription: 16 upvotes on Hugging Face Daily Papers, #7 of 15 papers on 2026-07-15. Day-by-day upvote history. It lost 9 votes when the Hub removed votes in bulk.

Existing methods for automatic music transcription are often limited to single-instrument recordings or fail on complex, real music mixes. Although previous work utilizes synthetic training data, the resulting models generalize poorly, leading to largely unusable transcription output in realistic, multi-instrument settings. In this work, we analyze the effectiveness of synthetic data for pre-training while combining it with fine-tuning on real music audio and post-training using reinforcement learning. We further introduce conditioning on instrument presence to customize transcriptions. Finally, we release MuScriptor, an open-weight multi-instrument music transcription model that works on real-world music recordings from across a diverse range of musical genres.

Paper page on Hugging Face · arXiv

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