Perform critical band analysis (see PLP), which means the reduction of the
fourier frequencies of a signal's powerspectrum to a reduced number of frequency
bands in an auditory frequency scale.
audspec(pspectrum, sr = 16000, nfilts = ceiling(hz2bark(sr/2)) + 1,
fbtype = c("bark", "mel", "htkmel", "fcmel"), minfreq = 0,
maxfreq = sr/2, sumpower = TRUE, bwidth = 1)
Matrix with the auditory spectrum of each time frame in its columns.
Weight matrix for the frequency band conversion.
Output of powspec, matrix with the powerspectrum of each time frame in its columns.
Sample rate of the original recording.
Number of filters/frequency bins in the auditory frequency scale.
Used auditory frequency scale.
If sumpower = TRUE, the frequency scale transformation is based on the
powerspectrum, if sumpower = FALSE, it is based on its squareroot (absolute value of the spectrum) and
sumpower = TRUE
sumpower = FALSE
Modify the width of the frequency bands.
Sebastian Krey email@example.com
Daniel P. W. Ellis: https://www.ee.columbia.edu/~dpwe/resources/matlab/rastamat/
testsound <- normalize(sine(400) + sine(1000) + square(250), "16")
pspectrum <- powspec(testsound@left, firstname.lastname@example.org)
aspectrum <- audspec(pspectrum, email@example.com)
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