functional_phase_vocoder: Phase Vocoder

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

Phase Vocoder

Description

Given a STFT tensor, speed up in time without modifying pitch by a factor of rate.

Usage

functional_phase_vocoder(complex_specgrams, rate, phase_advance)

Arguments

complex_specgrams	(Tensor): Dimension of ⁠(..., freq, time, complex=2)⁠
rate	(float): Speed-up factor
phase_advance	(Tensor): Expected phase advance in each bin. Dimension of (freq, 1)

Value

tensor: Complex Specgrams Stretch with dimension of ⁠(..., freq, ceiling(time/rate), complex=2)⁠

Examples

if(torch::torch_is_installed()) {
library(torch)
library(torchaudio)

freq = 1025
hop_length = 512

#  (channel, freq, time, complex=2)
complex_specgrams = torch_randn(2, freq, 300, 2)
rate = 1.3 # Speed up by 30%
phase_advance = torch_linspace(0, pi * hop_length, freq)[.., NULL]
x = functional_phase_vocoder(complex_specgrams, rate, phase_advance)
x$shape # with 231 == ceil (300 / 1.3)
# torch.Size ([2, 1025, 231, 2])
}

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