Brief

Researchers have developed a new music transcription model that significantly reduces the need for paired audio-score data. By employing a cycle-consistent translation framework and leveraging vast amounts of unpaired audio and symbolic scores, the model achieves substantial gains, particularly with limited supervision. The study also found that incorporating unlabeled audio from new instruments during training improves transcription for those instruments without requiring any paired data. AI