Neural Egg Separation: Training ML systems to extract audio/video from noisy/cluttered environments

Introduced Neural Egg Separation (NES), a semi-supervised iterative method for isolating audio and visual sources in noisy environments. NES combines aspects of supervised training and estimation by mixing signals and conducting multiple analyses, gradually injecting known signals while the model improves at extraction. Experiments show NES outperforms other methods with similar supervision levels and is competitive with fully supervised systems.