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log-spectral amplitude (Ephraim & Malah 1985) or Wiener (Scalart & Filho 1996) gain on the decision-directed a priori SNR ξ = α·Â²(l−1)/λ(l−1) + (1−α)·max(γ−1, 0) (Ephraim & Malah 1984, eq. 51). The noise PSD λ is tracked by minimum statistics (Martin 2001) over a 1.5 s window, in batch and stream alike, unless a profile or a noise-only stretch is given.\n\n```js\nwiener(data, { fs })                                           // LSA gain, noise tracked\nwiener(data, { fs, rule: 'wiener' })                           // Wiener gain\nwiener(data, { fs, noiseFrames: 6 })                           // noise from the first 6 frames\n```\n\n| Param | Default | |\n|---|---|---|\n| `rule` | `'mmse-lsa'` | `'wiener'` or `'mmse-lsa'` (log-spectral, less musical noise) |\n| `alpha` | `0.98` | Decision-directed smoothing (alias of `alphaDD`) |\n| `xiMin` | `10^−1.5` | A priori SNR floor (−15 dB) |\n| `frameSize` | power of two nearest 32 ms | STFT frame: 512 at 16 and 22.05 kHz, 1024 at 44.1, 2048 at 48 (`frame(fs)`) |\n| `hopSize` | `frameSize/4` | OLA hop |\n| `profile` | tracked | Noise PSD (`Float64Array`, `frameSize/2+1` bins) |\n| `noiseFrames` / `profileFrom` / `profileTo` | | A noise-only stretch to average for the profile |\n\n**Use when:** transparent broadband denoise; the \"safe default\" for stationary noise.\n\n---\n\nPart of [@audio/denoise](https://github.com/audiojs/denoise) — the denoise family umbrella. This README is generated from the umbrella docs.\n\nMIT © [audiojs](https://github.com/audiojs)\n","readmeFilename":"README.md"}