soundgen (version 2.7.2)

bandpass: Bandpass/stop filters

Description

Filtering in the frequency domain with FFT-iFFT: low-pass, high-pass, bandpass, and bandstop filters. Similar to ffilter, but here we use FFT instead of STFT - that is, the entire sound is processed at once. This works best for relatively short sounds (seconds), but gives us maximum precision (e.g., for precise notch filtering) and doesn't affect the attack and decay. NAs are accepted and can be interpolated or preserved in the output. Because we don't do STFT, arbitrarily short vectors are also fine as input - for example, we can apply a low-pass filter prior to decimation when changing the sampling rate without aliasing. Note that, unlike pitchSmoothPraat, bandpass by default applies an abrupt cutoff instead of a smooth gaussian filter, but this behavior can be adjusted with the bw argument.

Usage

bandpass(
  x,
  samplingRate = NULL,
  lwr = NULL,
  upr = NULL,
  action = c("pass", "stop")[1],
  dB = Inf,
  bw = 0,
  na.rm = TRUE,
  from = NULL,
  to = NULL,
  normalize = FALSE,
  reportEvery = NULL,
  cores = 1,
  saveAudio = NULL,
  plot = FALSE,
  savePlots = NULL,
  width = 900,
  height = 500,
  units = "px",
  res = NA,
  ...
)

Arguments

x

path to a folder, one or more wav or mp3 files c('file1.wav', 'file2.mp3'), Wave object, numeric vector, or a list of Wave objects or numeric vectors

samplingRate

sampling rate of x (only needed if x is a numeric vector)

lwr, upr

cutoff frequencies, Hz. Specifying just lwr gives a high-pass filter, just upr low-pass filter with action = 'pass' (or vice versa with action = 'stop'). Specifying both lwr and upr a bandpass/bandstop filter, depending on 'action'

action

"pass" = preserve the selected frequency range (bandpass), "stop" = remove the selected frequency range (bandstop)

dB

a positive number giving the strength of effect in dB (defaults to Inf - complete removal of selected frequencies)

bw

bandwidth of the filter cutoffs, Hz. Defaults to 0 (abrupt, step function), a positive number corresponds to the standard deviation of a Gaussian curve, and two numbers set different bandwidths for the lower and upper cutoff points

na.rm

if TRUE, NAs are interpolated, otherwise they are preserved in the output

from, to

if NULL (default), analyzes the whole sound, otherwise from...to (s)

normalize

if TRUE, resets the output to the original scale (otherwise filtering often reduces the amplitude)

reportEvery

when processing multiple inputs, report estimated time left every ... iterations (NULL = default, NA = don't report)

cores

number of cores for parallel processing

saveAudio

full path to the folder in which to save the processed audio

plot

should a spectrogram be plotted? TRUE / FALSE

savePlots

full path to the folder in which to save the plots (NULL = don't save, '' = same folder as audio)

width, height, units, res

graphical parameters for saving plots passed to png

...

other graphical parameters passed to plot() as well as to meanspec

Details

Algorithm: fill in NAs with constant interpolation at the edges and linear interpolation in the middle; perform FFT; set the frequency ranges to be filtered out to 0; perform inverse FFT; set to the original scale; put the NAs back in.

Examples

# Filter white noise
s1 = fade(c(rnorm(2000, 0, 1)), samplingRate = 16000)

# low-pass
bandpass(s1, 16000, upr = 2000, plot = TRUE)

# high-pass by 40 dB
bandpass(s1, 16000, lwr = 2000, dB = 40, plot = TRUE, wl = 1024)
# wl is passed to seewave::meanspec for plotting

# bandstop
bandpass(s1, 16000, lwr = 1000, upr = 1800, action = 'stop', plot = TRUE)

# bandpass
s2 = bandpass(s1, 16000, lwr = 2000, upr = 2100, plot = TRUE)
# playme(rep(s2, 5))
# spectrogram(s2, 16000)

# low-pass and interpolate a short vector with some NAs
x = rnorm(150, 10) + 3 * sin((1:50) / 5)
x[sample(seq_along(x), 50)] = NA
plot(x, type = 'l')
x_bandp = bandpass(x, samplingRate = 100, upr = 10)
points(x_bandp, type = 'l', col = 'blue')

if (FALSE) {
# add 20 dB with a Gaussian-shaped filter instead of step function
s3 = bandpass(s1, 16000, lwr = 1700, upr = 2100, bw = 200,
  dB = 20, plot = TRUE)
spectrogram(s3, 16000)
s4 = bandpass(s1, 16000, lwr = 2000, upr = 4300, bw = c(100, 500),
  dB = 60, action = 'stop', plot = TRUE)
spectrogram(s4, 16000)

# precise notch filtering is possible, even in low frequencies
whiteNoise = runif(16000, -1, 1)
s3 = bandpass(whiteNoise, 16000, lwr = 30, upr = 40, normalize = TRUE,
              plot = TRUE, xlim = c(0, 500))
playme(rep(s3, 5))
spectrogram(s3, 16000, windowLength = 150, yScale = 'log')

# compare the same with STFT
s4 = seewave::ffilter(whiteNoise, f = 16000, from = 30, to = 40)
spectrogram(s4, 16000, windowLength = 150, yScale = 'log')
# (note: works better as wl approaches length(s4))

# high-pass all audio files in a folder
bandpass('~/Downloads/temp', saveAudio = '~/Downloads/temp/hp2000/',
         lwr = 2000, savePlots = '~/Downloads/temp/hp2000/')
}