音源分離

Open-Unmix HQ はステレオ音楽トラックを 4 つの独立したステム — ボーカル、ドラム、ベース、その他 に分離します。独立した 4 つの BiLSTM モデル（各ステムに 1 つ）がミックス STFT 上でマグニチュードマスクを生成し、任意の Wiener 後処理で整合させます。MLX で Apple Silicon 上動作します。

概要

• 4 stems per track — vocals, drums, bass, other. Each is a 2-channel 44.1 kHz stem file.
• Magnitude-mask model — each stem model predicts a non-negative mask applied to the mixture spectrogram; phase is taken from the mixture.
• Wiener post-filter (optional) — soft-mask refinement across all 4 stems so they sum coherently back to the mixture. Adds ~0.5 dB SDR.
• Small footprint — 8.9M params per stem, ~136 MB total for all 4 stems.
• Apache-2.0 — upstream weights under MIT, our CoreML/MLX conversion under Apache-2.0.

アーキテクチャ

Four independent stems, each a copy of the same network:

モデル

クイックスタート — Swift

import SourceSeparation
import AudioCommon

let separator = try await SourceSeparator.fromPretrained()

let stereo = try AudioFileLoader.loadStereo(
    url: URL(fileURLWithPath: "song.wav"),
    targetSampleRate: 44100
)

let stems = separator.separate(audio: stereo, sampleRate: 44100)
// stems[.vocals], stems[.drums], stems[.bass], stems[.other]
// Each is [[Float]] — left channel, right channel.

try WAVWriter.writeStereo(
    left: stems[.vocals]![0],
    right: stems[.vocals]![1],
    sampleRate: 44100,
    to: URL(fileURLWithPath: "vocals.wav")
)

Pass wiener: true (default) for best quality. Pass targets: [.vocals] to extract only a subset of stems and skip the other models.

コマンドライン

speech separate song.wav                              # all 4 stems into song_stems/
speech separate song.wav --stems vocals               # vocals only
speech separate song.wav --stems vocals,drums         # subset
speech separate song.wav --output-dir /tmp/stems/     # custom output dir
speech separate song.wav --verbose                    # show timing

使用タイミング