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Ahmed Doghri

restem

A separator does not need retraining to take a second pass. restem iteratively removes residual interference and adds 27.74 dB of SNR.

restem reproduced benchmark result

One Pass Leaves Music On The Vocal

Most source separators make one prediction and stop, even when the output still contains structured leakage the same separator knows how to recognize.

restem synthesizes a vocal and backing source, writes their mixture to WAV, and starts with a one-step estimate that contains measurable backing interference.

Run The Separator Again, Carefully

Each pass estimates the remaining high-frequency leakage and removes a conservative fraction. The update is explicit, so the improvement curve can be inspected instead of heard by faith.

This follows the paper's training-free multi-step principle at signal level. It is not presented as a replacement for Demucs or a learned separator.

The Number

The one-step estimate measures 8.78 dB SNR. Five total passes reach 36.52 dB, a 27.74 dB gain.

The repository commits `mixture.wav` and `separated.wav`, so the artifact is playable as well as measurable. The test reproduces both files in CI.

Research Basis

Inspired by the 2025 training-free multi-step separation paper. The portfolio number above comes from this repository's own controlled benchmark, not from the paper.

Tools Used

Python
Audio DSP
Source Separation
WAV
Iterative Refinement
unittest
GitHub Actions CI