Towards Human-in-the-Loop Onset Detection: A Transfer Learning Approach for Maracatu

• URL: http://arxiv.org/abs/2507.04858v1
• Date: Mon, 07 Jul 2025 10:32:26 GMT
• Title: Towards Human-in-the-Loop Onset Detection: A Transfer Learning Approach for Maracatu
• Authors: António Sá Pinto,
• Abstract summary: We explore transfer learning strategies for musical onset detection in the Afro-Brazilian Maracatu tradition.<n>We adapt two Temporal Convolutional Network architectures: one pre-trained for onset detection (intra-task) and another for beat tracking (inter-task)<n>Using only 5-second annotated snippets per instrument, we fine-tune these models through layer-wise retraining strategies for five traditional percussion instruments.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We explore transfer learning strategies for musical onset detection in the Afro-Brazilian Maracatu tradition, which features complex rhythmic patterns that challenge conventional models. We adapt two Temporal Convolutional Network architectures: one pre-trained for onset detection (intra-task) and another for beat tracking (inter-task). Using only 5-second annotated snippets per instrument, we fine-tune these models through layer-wise retraining strategies for five traditional percussion instruments. Our results demonstrate significant improvements over baseline performance, with F1 scores reaching up to 0.998 in the intra-task setting and improvements of over 50 percentage points in best-case scenarios. The cross-task adaptation proves particularly effective for time-keeping instruments, where onsets naturally align with beat positions. The optimal fine-tuning configuration varies by instrument, highlighting the importance of instrument-specific adaptation strategies. This approach addresses the challenges of underrepresented musical traditions, offering an efficient human-in-the-loop methodology that minimizes annotation effort while maximizing performance. Our findings contribute to more inclusive music information retrieval tools applicable beyond Western musical contexts.

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