Frequency band conversion

Description

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.

Usage

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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)

Arguments

pspectrum

Output of powspec, matrix with the powerspectrum of each time frame in its columns.

sr

Sample rate of the original recording.

nfilts

Number of filters/frequency bins in the auditory frequency scale.

fbtype

Used auditory frequency scale.

minfreq

Lowest frequency.

maxfreq

Highest frequency.

sumpower

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 squared afterwards.

bwidth

Modify the width of the frequency bands.

Value

aspectrum

Matrix with the auditory spectrum of each time frame in its columns.

wts

Weight matrix for the frequency band conversion.

Author(s)

Sebastian Krey krey@statistik.tu-dortmund.de

References

Daniel P. W. Ellis: http://www.ee.columbia.edu/~dpwe/resources/matlab/rastamat/

See Also

fft2melmx, fft2barkmx

Examples

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  testsound <- normalize(sine(400) + sine(1000) + square(250), "16")
  pspectrum <- powspec(testsound@left, testsound@samp.rate)
  aspectrum <- audspec(pspectrum, testsound@samp.rate)

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