Convert Hertz to Bark and Bark to Hertz
The calculation is done using the formulae Traunmueller (1990)
bark(f, inv = FALSE, ...)
f |
A vector or matrix of data or a spectral object. |
inv |
A single element logical vector. If F, data are converted from Hertz to Bark, if T, data are converted from Bark to Hertz. (Does not apply if 'data' is an oject of class 'spectral'. |
... |
for generic only |
If 'data' is a spectral object, then
the frequencies are changed so that they are proportional
to the Bark scale and such that the Bark intervals
between frequencies are con stant between the lowest
and highest frequencies. More specifically,
suppose that a spectral object has frequencies
at 0, 1000, 2000, 3000, 4000 Hz. Then the corresponding
frequencies extend in Bark between 0 and 17.46329 Bark
in four equal intervals, and linear interpolation
is used with the 'approx' function to obtain
the dB values at those frequencies. Negative frequencies
which are obtained for values of about less than 40 Hz
are removed in the case of spectral objects.
A vector or matrix or spectral object of the same length and dimensions as data.
Jonathan Harrington
Traunmueller, H. (1990) "Analytical expressions for the tonotopic sensory scale" J. Acoust. Soc. Am. 88: 97-100.
mel,
# convert Hertz values to Bark
vec <- c(500, 1500, 2500)
vec
bark(vec)
# convert Hertz values to Bark and back to Hertz
bark(bark(vec, inv=TRUE))
# convert the \$data values in a trackdata object to Bark
# create a new track data object
t1 <- dip.fdat
t1[1]
# convert Hertz to Bark
t1$data <- bark(t1$data)
t1[1]
# warp the frequency axis of a spectral object such
# that it is proportional to the Bark scale.
w = bark(e.dft)
par(mfrow=c(1,2))
plot(w, type="l")
# The values of w are at equal Bark intervals. Compare
# with
plot(e.dft, freq=bark(trackfreq(e.dft)))
# the latter has a greater concentration of values
# in a higher frequency range.Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.