csh {seewave}

Continuous spectral entropy

Description

This function computes the continuous spectral entropy (H) of a time wave.

Usage

csh(wave, f, channel = 1, wl = 512, wn = "hanning", ovlp = 0,
fftw = FALSE, threshold = NULL,
plot = TRUE, xlab = "Times (s)", ylab = "Spectral Entropy",
ylim = c(0, 1.1), type = "l", ...)

Arguments

wave

an R object.

f

sampling frequency of wave (in Hz). Does not need to be specified if embedded in wave.

channel

channel of the R object, by default left channel (1).

wl

if at is not null, length of the window for the analysis (even number of points, by default = 512).

wn

window name, see ftwindow (by default "hanning").

ovlp

overlap between two successive windows (in %).

fftw

if TRUE calls the function FFT of the library fftw. See Notes of the spectro.

threshold

amplitude threshold for signal detection (in %).

plot

logical, if TRUE plots the spectral entropy against time (by default TRUE).

xlab

title of the x axis.

ylab

title of the y axis.

ylim

the range of y values.

type

if plot is TRUE, type of plot that should be drawn. See plot for details (by default "l" for lines).

...

other plot graphical parameters.

Details

See sh for computing method.

Value

When plot is FALSE, csh returns a two-column matrix, the first column being time in seconds (x-axis) and the second column being the spectral entropy (y-axis) computed along time.
NA corresponds to pause sections in wave (see threshold).

Note

The spectral entropy of a noisy signal will tend towards 1 whereas the spectral entropy of a pure tone signal will tend towards 0.

Author(s)

Jerome Sueur [e-mail]

References

Toh, A. M., Togneri, R. & Nordholm, S. 2005 Spectral entropy as speech features for speech recognition. Proceedings of PEECS, pp. 60-65.

See Also

sh, th

Examples

data(orni)
csh(orni,f=22050,wl=512,ovlp=50)
# using the threshold argument can lead to some edge effets
# here sh=1 at the end of echemes
csh(orni,f=22050,wl=512,ovlp=50,threshold=5)