Phase Cancellation vs AI Masking: Benchmarking Vocal Removal Methods in Python

A developer compares two approaches to removing vocals from a finished stereo mix: a classic phase-cancellation trick and modern AI source separation. Using a synthetic six-second arrangement where every source is known, the author scores each method with SI-SDR, a standard source-separation metric. A naive mid/side cancellation performed worse than doing nothing, but adding band-limited cancellation and bass preservation raised the instrumental score substantially. The method breaks down with stereo reverb, where left and right tails differ and leave a faint 'ghost vocal'. The article then turns to spectrogram-masking models like Open-Unmix, Demucs and MDX-style networks, which estimate per-bin energy for each source.