functional_spectrogram: Spectrogram (functional)

In curso-r/torchaudio: R Interface to 'pytorch''s 'torchaudio'

Spectrogram (functional)

Description

Create a spectrogram or a batch of spectrograms from a raw audio signal. The spectrogram can be either magnitude-only or complex.

Usage

functional_spectrogram(
  waveform,
  pad,
  window,
  n_fft,
  hop_length,
  win_length,
  power,
  normalized
)

Arguments

waveform	(tensor): Tensor of audio of dimension (..., time)
pad	(integer): Two sided padding of signal
window	(tensor or function): Window tensor that is applied/multiplied to each frame/window or a function that generates the window tensor.
n_fft	(integer): Size of FFT
hop_length	(integer): Length of hop between STFT windows
win_length	(integer): Window size
power	(numeric): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2 for power, etc. If NULL, then the complex spectrum is returned instead.
normalized	(logical): Whether to normalize by magnitude after stft

Value

tensor: Dimension (..., freq, time), freq is n_fft %/% 2 + 1 and n_fft is the number of Fourier bins, and time is the number of window hops (n_frame).

curso-r/torchaudio documentation built on May 4, 2023, 2:27 a.m.