Azalea (Yijie) Gui

TOWARDS BLIND DATA CLEANING: A CASE STUDY IN MUSIC SOURCE SEPARATION

The performance of deep learning models for music source separation heavily depends on training data quality. However, datasets are often corrupted by difficult-to-detect artifacts such as audio bleeding and label noise. Since the type and extent of contamination are typically unknown, cleaning meth…