audSpectrogram: Auditory spectrogram

In soundgen: Sound Synthesis and Acoustic Analysis

Auditory spectrogram

Description

Produces an auditory spectrogram by convolving the sound with a bank of bandpass filters. The main difference from STFT is that we don't window the signal and de facto get variable temporal resolution in different frequency channels, as with a wavelet transform. The key settings are filterType, nFilters, and yScale, which determine the type, number, and spacing of the filters, respectively. Gammatone filters were designed as a simple approximation of human perception - see gammatone and Slaney 1993 "An Efficient Implementation of the Patterson–Holdsworth Auditory Filter Bank". Butterworth or Chebyshev filters are not meant to model perception, but can be useful for quickly plotting a sound.

Usage

audSpectrogram(
  x,
  samplingRate = NULL,
  scale = NULL,
  from = NULL,
  to = NULL,
  step = 1,
  dynamicRange = 80,
  filterType = c("butterworth", "chebyshev", "gammatone")[1],
  nFilters = 128,
  nFilters_oct = NULL,
  filterOrder = if (filterType == "gammatone") 4 else 3,
  bandwidth = NULL,
  bandwidthMult = 1,
  minFreq = 20,
  maxFreq = samplingRate/2,
  minBandwidth = 10,
  output = c("audSpec", "audSpec_processed", "filterbank", "filterbank_env", "roughness"),
  reportEvery = NULL,
  cores = 1,
  plot = TRUE,
  savePlots = NULL,
  plotFilters = FALSE,
  osc = c("none", "linear", "dB")[2],
  heights = c(3, 1),
  ylim = NULL,
  yScale = c("bark", "mel", "ERB", "log")[1],
  contrast = 0.2,
  brightness = 0,
  maxPoints = c(1e+05, 5e+05),
  padWithSilence = TRUE,
  colorTheme = c("bw", "seewave", "heat.colors", "...")[1],
  col = NULL,
  extraContour = NULL,
  xlab = NULL,
  ylab = NULL,
  xaxp = NULL,
  mar = c(5.1, 4.1, 4.1, 2),
  main = NULL,
  grid = 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)
scale	maximum possible amplitude of input used for normalization of input vector (only needed if x is a numeric vector)
from, to	if NULL (default), analyzes the whole sound, otherwise from...to (s)
step	step, ms (determines time resolution of the plot, but not of the returned envelopes per channel). step = NULL means no downsampling at all (ncol of output = length of input audio)
dynamicRange	dynamic range, dB. All values more than one dynamicRange under maximum are treated as zero
filterType	"butterworth" = Butterworth filter butter, "chebyshev" = Chebyshev filter butter, "gammatone" = gammatone
nFilters	the number of filters between minFreq and maxFreq (determines frequency resolution, while yScale determines the location of center frequencies)
nFilters_oct	an alternative way to specify frequency resolution: the number of filters per octave
filterOrder	filter order (defaults to 4 for gammatones, 3 otherwise)
bandwidth	filter bandwidth, octaves. If NULL, defaults to ERB bandwidths as in gammatone
bandwidthMult	a scaling factor for all bandwidths (1 = no effect)
minFreq, maxFreq	the range of frequencies to analyze
minBandwidth	minimum filter bandwidth, Hz (otherwise filters may become too narrow when nFilters is high; has no effect if filterType = 'gammatone')
output	a list of measures to return. Defaults to everything, but this takes a lot of RAM, so shorten to what's needed if analyzing many files at once
reportEvery	when processing multiple inputs, report estimated time left every ... iterations (NULL = default, NA = don't report)
cores	number of cores for parallel processing
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)
plotFilters	if TRUE, plots the filters as central frequencies ± bandwidth/2
osc	"none" = no oscillogram; "linear" = on the original scale; "dB" = in decibels
heights	a vector of length two specifying the relative height of the spectrogram and the oscillogram (including time axes labels)
ylim	frequency range to plot, kHz (defaults to 0 to Nyquist frequency). NB: still in kHz, even if yScale = bark, mel, or ERB
yScale	determines the location of center frequencies of the filters
contrast	spectrum is exponentiated by contrast (any real number, recommended -1 to +1). Contrast >0 increases sharpness, <0 decreases sharpness
brightness	how much to "lighten" the image (>0 = lighter, <0 = darker)
maxPoints	the maximum number of "pixels" in the oscillogram (if any) and spectrogram; good for quickly plotting long audio files; defaults to c(1e5, 5e5)
padWithSilence	if TRUE, pads the sound with just enough silence to resolve the edges properly (only the original region is plotted, so the apparent duration doesn't change)
colorTheme	black and white ('bw'), as in seewave package ('seewave'), matlab-type palette ('matlab'), or any palette from palette such as 'heat.colors', 'cm.colors', etc
col	actual colors, eg rev(rainbow(100)) - see ?hcl.colors for colors in base R (overrides colorTheme)
extraContour	a vector of arbitrary length scaled in Hz (regardless of yScale!) that will be plotted over the spectrogram (eg pitch contour); can also be a list with extra graphical parameters such as lwd, col, etc. (see examples)
xlab, ylab, main, mar, xaxp	graphical parameters for plotting
grid	if numeric, adds n = grid dotted lines per kHz
width, height, units, res	graphical parameters for saving plots passed to png
...	other graphical parameters

Value

Returns a list for each analyzed file, including:

audSpec

auditory spectrogram with frequencies in rows and time in columns

audSpec_processed

same but rescaled for plotting

filterbank

raw output of the filters

roughness

roughness per channel (as many as nFilters)

Examples

# synthesize a sound with gradually increasing hissing noise
sound = soundgen(sylLen = 200, temperature = 0.001,
  noise = list(time = c(0, 350), value = c(-40, 0)),
  formantsNoise = list(f1 = list(freq = 5000, width = 10000)),
  addSilence = 25)
# playme(sound, samplingRate = 16000)

# auditory spectrogram
as = audSpectrogram(sound, samplingRate = 16000, nFilters = 48)
dim(as$audSpec)

# compare to FFT-based spectrogram with similar time and frequency resolution
fs = spectrogram(sound, samplingRate = 16000, yScale = 'bark',
                 windowLength = 5, step = 1)
dim(fs)

## Not run: 
# add bells and whistles
audSpectrogram(sound, samplingRate = 16000,
  filterType = 'gammatone',
  nFilters = 50,
  yScale = 'ERB',
  bandwidth = 1/12,
  dynamicRange = 150,
  osc = 'dB',  # plot oscillogram in dB
  heights = c(2, 1),  # spectro/osc height ratio
  contrast = .2,  # increase contrast
  brightness = -.1,  # reduce brightness
  # colorTheme = 'heat.colors',  # pick color theme...
  col = hcl.colors(100, palette = 'Plasma'),  # ...or specify the colors
  cex.lab = .75, cex.axis = .75,  # text size and other base graphics pars
  grid = 5,  # to customize, add manually with graphics::grid()
  ylim = c(0.05, 8),  # always in kHz
  main = 'My auditory spectrogram' # title
  # + axis labels, etc
)

# NB: frequency resolution is controlled by both nFilters and bandwidth
audSpectrogram(sound, 16000, nFilters = 15, bandwidth = 1/2)
audSpectrogram(sound, 16000, nFilters = 15, bandwidth = 1/10)
audSpectrogram(sound, 16000, nFilters = 100, bandwidth = 1/2)
audSpectrogram(sound, 16000, nFilters = 100, bandwidth = 1/10)
audSpectrogram(sound, 16000, nFilters_oct = 5, bandwidth = 1/10)

# remove the oscillogram
audSpectrogram(sound, samplingRate = 16000, osc = 'none')

# save auditory spectrograms of all audio files in a folder
audSpectrogram('~/Downloads/temp',
  savePlots = '~/Downloads/temp/audSpec', cores = 4)

## End(Not run)

soundgen documentation built on Sept. 12, 2024, 6:29 a.m.