soundgen (version 2.4.0)

spectrogram: Spectrogram

Description

Produces the spectrogram of a sound using short-time Fourier transform. Inspired by spectro, this function offers added routines for noise reduction, smoothing in time and frequency domains, manual control of contrast and brightness, plotting the oscillogram on a dB scale, grid, etc.

Usage

spectrogram(
  x,
  samplingRate = NULL,
  scale = NULL,
  from = NULL,
  to = NULL,
  dynamicRange = 80,
  windowLength = 50,
  step = NULL,
  overlap = 70,
  wn = "gaussian",
  zp = 0,
  normalize = TRUE,
  smoothFreq = 0,
  smoothTime = 0,
  qTime = 0,
  percentNoise = 10,
  noiseReduction = 0,
  method = c("spectrum", "spectralDerivative")[1],
  output = c("original", "processed", "complex")[1],
  reportEvery = NULL,
  plot = TRUE,
  savePlots = NULL,
  osc = c("none", "linear", "dB")[2],
  heights = c(3, 1),
  ylim = NULL,
  yScale = c("linear", "log", "bark", "mel")[1],
  contrast = 0.2,
  brightness = 0,
  maxPoints = c(1e+05, 5e+05),
  padWithSilence = TRUE,
  colorTheme = c("bw", "seewave", "heat.colors", "...")[1],
  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)

dynamicRange

dynamic range, dB. All values more than one dynamicRange under maximum are treated as zero

windowLength

length of FFT window, ms

step

you can override overlap by specifying FFT step, ms (NB: because digital audio is sampled at discrete time intervals of 1/samplingRate, the actual step and thus the time stamps of STFT frames may be slightly different, eg 24.98866 instead of 25.0 ms)

overlap

overlap between successive FFT frames, %

wn

window type accepted by ftwindow, currently gaussian, hanning, hamming, bartlett, rectangular, blackman, flattop

zp

window length after zero padding, points

normalize

if TRUE, scales input prior to FFT

smoothFreq, smoothTime

length of the window for median smoothing in frequency and time domains, respectively, points

qTime

the quantile to be subtracted for each frequency bin. For ex., if qTime = 0.5, the median of each frequency bin (over the entire sound duration) will be calculated and subtracted from each frame (see examples)

percentNoise

percentage of frames (0 to 100%) used for calculating noise spectrum

noiseReduction

how much noise to remove (non-negative number, recommended 0 to 2). 0 = no noise reduction, 2 = strong noise reduction: \(spectrum - (noiseReduction * noiseSpectrum)\), where noiseSpectrum is the average spectrum of frames with entropy exceeding the quantile set by percentNoise

method

plot spectrum ('spectrum') or spectral derivative ('spectralDerivative')

output

specifies what to return: nothing ('none'), unmodified spectrogram ('original'), denoised and/or smoothed spectrogram ('processed'), or unmodified spectrogram with the imaginary part giving phase ('complex')

reportEvery

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

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)

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 or mel

yScale

scale of the frequency axis: 'linear' = linear, 'log' = logarithmic (musical), 'bark' = bark with hz2bark, 'mel' = mel with hz2mel

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'), or any palette from palette such as 'heat.colors', 'cm.colors', etc

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 nothing (if output = 'none'), absolute - not power! - spectrum (if output = 'original'), denoised and/or smoothed spectrum (if output = 'processed'), or spectral derivatives (if method = 'spectralDerivative') as a matrix of real numbers.

Details

Many soundgen functions call spectrogram, and you can pass along most of its graphical parameters from functions like soundgen, analyze, etc. However, in some cases this will not work (eg for "units") or may produce unexpected results. If in doubt, omit extra graphical parameters.

See Also

osc modulationSpectrum ssm

Examples

# NOT RUN {
# synthesize a sound 500 ms long, with gradually increasing hissing noise
sound = soundgen(sylLen = 500, temperature = 0.001, noise = list(
  time = c(0, 650), value = c(-40, 0)), formantsNoise = list(
  f1 = list(freq = 5000, width = 10000)))
# playme(sound, samplingRate = 16000)

# basic spectrogram
spectrogram(sound, samplingRate = 16000, yScale = 'bark')

# add bells and whistles
spectrogram(sound, samplingRate = 16000,
  osc = 'dB',  # plot oscillogram in dB
  heights = c(2, 1),  # spectro/osc height ratio
  noiseReduction = 1.1,  # subtract the spectrum of noisy parts
  brightness = -1,  # reduce brightness
  colorTheme = 'heat.colors',  # pick color theme
  cex.lab = .75, cex.axis = .75,  # text size and other base graphics pars
  grid = 5,  # lines per kHz; to customize, add manually with graphics::grid()
  ylim = c(0, 5),  # always in kHz
  main = 'My spectrogram' # title
  # + axis labels, etc
)
# }
# NOT RUN {
# change dynamic range
spectrogram(sound, samplingRate = 16000, dynamicRange = 40)
spectrogram(sound, samplingRate = 16000, dynamicRange = 120)

# remove the oscillogram
spectrogram(sound, samplingRate = 16000, osc = 'none')  # or NULL etc

# frequencies on a logarithmic (musical) scale (mel/bark also available)
spectrogram(sound, samplingRate = 16000,
            yScale = 'log', ylim = c(.05, 8))

# broad-band instead of narrow-band
spectrogram(sound, samplingRate = 16000, windowLength = 5)

# focus only on values in the upper 5% for each frequency bin
spectrogram(sound, samplingRate = 16000, qTime = 0.95)

# detect 10% of the noisiest frames based on entropy and remove the pattern
# found in those frames (in this cases, breathing)
spectrogram(sound, samplingRate = 16000,  noiseReduction = 1.1,
  brightness = -2)  # white noise attenuated

# apply median smoothing in both time and frequency domains
spectrogram(sound, samplingRate = 16000, smoothFreq = 5,
  smoothTime = 5)

# increase contrast, reduce brightness
spectrogram(sound, samplingRate = 16000, contrast = 1, brightness = -1)

# specify location of tick marks etc - see ?par() for base graphics
spectrogram(sound, samplingRate = 16000,
            ylim = c(0, 3), yaxp = c(0, 3, 5), xaxp = c(0, .8, 10))

# Plot long audio files with reduced resolution
data(sheep, package = 'seewave')
sp = spectrogram(sheep, overlap = 0,
  maxPoints = c(1e4, 5e3),  # limit the number of pixels in osc/spec
  output = 'original')
nrow(sp) * ncol(sp) / 5e3  # spec downsampled by a factor of ~2

# Plot some arbitrary contour over the spectrogram (simply calling lines()
# will not work if osc = TRUE b/c the plot layout is modified)
s = soundgen()
an = analyze(s, 16000, plot = FALSE)
spectrogram(s, 16000, extraContour = an$detailed$dom, ylim = c(0, 2), yScale = 'bark')
# For values that are not in Hz, normalize any way you like
spectrogram(s, 16000, ylim = c(0, 2), extraContour = list(
  x = an$detailed$loudness / max(an$detailed$loudness, na.rm = TRUE) * 2000,
  # ylim[2] = 2000 Hz
  type = 'b', pch = 5, lwd = 2, lty = 2, col = 'blue'))
# }