Alapfogalmak
Enhancing multi-instrument music transcription with MR-MT3 to mitigate instrument leakage.
Kivonat
The paper introduces MR-MT3 as an enhancement to the MT3 model for multi-instrument automatic music transcription. It addresses the issue of instrument leakage by proposing a memory retention mechanism, prior token sampling, and token shuffling. These enhancements are evaluated on the Slakh2100 dataset, showing improved onset F1 scores and reduced instrument leakage. The study also introduces new metrics like the instrument leakage ratio and instrument detection F1 score for comprehensive assessment. The proposed methods aim to maintain musical context across audio segments, improving transcription quality.
Statisztikák
Onset F1 Scores: 62%
Instrument Leakage Ratio: 1.65
Precision: 28.5%
Recall: 45.2%
Idézetek
"Memory retention mechanism leverages past musical events to capture long-term context."
"Token shuffling serves as an effective data augmentation technique."
"Our proposed methods effectively improve onset F1 scores and reduce instrument leakage."