Full supervision models for source separation are trained on mixture-source parallel data and have achieved superior performance in recent years. However, large-scale and naturally mixed parallel training data are difficult to obtain for music, and such models are difficult to adapt to mixtures with new sources. Source-only supervision models, in contrast, only require clean sources for training; They learn source models and then apply these models to separate the mixture.

翻译：来源分离的全面监督模式在混合源平行数据方面受过培训,近年来取得了优异的成绩,然而,音乐很难获得大规模和自然混合的平行培训数据,这类模式难以适应新来源的混合物。