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Randomized Scores and Diverse Timbres: Augmenting Automatic Music Transcription with Online-Generated Data
Automatic music transcription (AMT) is limited by the scarcity of audio recordings paired with precise symbolic annotations. Synthetic data can provide supervision at scale, but it remains unclear whether effective transfer depends on realistic score structure or broad timbral coverage. We study the
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