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Pleco-Xa

Filter banks & windows

The filters namespace holds the reusable building blocks that the feature layer composes: the mel filterbank, the chroma filterbank, and the analysis windows. If feature is the “what,” filters is the “how” — the matrices and window functions you can pull out and apply yourself when building a custom pipeline.

Key functions

Section titled “Key functions”
  • filters.mel_filterbank(sr?, n_fft?, n_mels?, fmin?, fmax?, norm?, htk?) — the mel projection matrix: continuous Slaney triangular ramps over the FFT frequency grid with Slaney area normalization (HTK scale and other norms optional). Arguments are positional, defaulting to (22050, 2048, 128, 0, null, 'slaney', false). Multiply it against a power spectrogram to get a mel spectrogram.
  • filters.chroma({ sr, n_fft }) — the chroma filterbank: Gaussian pitch-class bumps with octave weighting and tuning. feature.chroma_stft is a matmul of this against the energy spectrum.
  • filters.get_window(type, n) — a window function (hann, hamming, blackman). Periodic by convention (fftbins=True), matching scipy — the correct choice for spectral analysis.

Example

Section titled “Example”
import { filters } from 'pleco-xa'


// build the mel matrix once, reuse across frames — positional args: (sr, n_fft, n_mels)
const melFb = filters.mel_filterbank(22050, 2048, 128)


// a periodic Hann window for your own STFT framing
const win = filters.get_window('hann', 2048)

Notes

Section titled “Notes”
  • mel_filterbank takes positional arguments, unlike the options-object style of the feature namespace. Passing an options object (mel_filterbank({ sr: 22050, ... })) does not throw — it silently produces a garbage matrix. Use the positional form shown above.
  • Windows are periodic (2π·i / n), not symmetric (/(n-1)). This is the scipy fftbins=True convention; the symmetric form skews every spectrogram bin.
  • The mel filterbank defaults to the Slaney scale with area normalization. Pass htk: true for the HTK scale.
  • These are the same filterbanks feature.melspectrogram and feature.chroma_stft use internally; exposing them lets you build custom feature stacks without re-deriving the matrices.

See the API reference for full signatures.