smst.models.stft module

Functions that implement analysis and synthesis of sounds using the Short-Time Fourier Transform.

For example usage check the stftModel_function module.

smst.models.stft.filter(x, fs, w, N, H, filter)

Applies a spectral filter to a sound by using the STFT.

Parameters:
  • x – input sound
  • w – analysis window
  • N – FFT size
  • H – hop size
  • filter – magnitude response of filter with frequency-magnitude pairs (in dB)
Returns:

y - output sound
smst.models.stft.from_audio(x, w, N, H)

Analyzes an input signal using the short-time Fourier transform into a spectrogram.

Parameters:
  • x – input signal
  • w – analysis window
  • N – FFT size
  • H – hop size
Returns:

mag_spectrogram, phase_spectrogram - magnitude and phase spectrograms
smst.models.stft.iterate_analysis_frames(x, H, hM1, hM2)

Iterate over frames of input signal for analysis.

Parameters:
  • x – input signal
  • H – hop size
  • hM1 – half analysis window size by rounding
  • hM2 – half analysis window size by floor
Returns:

generator over frames of input signal
smst.models.stft.morph(x1, x2, fs, w1, N1, w2, N2, H1, smoothf, balancef)

Morphs two sounds using the STFT.

Parameters:
  • x2 (x1,) – input sounds
  • fs – sampling rate
  • w2 (w1,) – analysis windows
  • N2 (N1,) – FFT sizes
  • H1 – hop size
  • smoothf – smooth factor of sound 2, bigger than 0 to max of 1, where 1 is no smoothing,
  • balancef – balance between the 2 sounds, from 0 to 1, where 0 is sound 1 and 1 is sound 2
Returns:

y: output sound
smst.models.stft.pad_signal(x, hM2)
smst.models.stft.to_audio(mY, pY, M, H)

Synthesizes an output signal from a spectrogram using the inverse short-time Fourier transform.

Parameters:
  • mY – magnitude spectrogram
  • pY – phase spectrogram
  • M – window size
  • H – hop-size
Returns:

y - output signal