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arXiv · 2607.08168

MuScriptor: An Open Model for Multi-Instrument Music Transcription

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

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.

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Simon Rouard, Michael Krause, Axel Roebel, Carl-Johann Simon-Gabriel, Alexandre Défossez. 2026-07-09. MuScriptor: An Open Model for Multi-Instrument Music Transcription. https://arxiv.org/abs/2607.08168

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