Matlab v_melbankm函數參數詳解(英文附例)

筆者使用的是R2019的matlab，下載了voicebox安裝至matlab路徑下即可使用。下載voicebox請參看此博客

需要注意的是，melbankm改成了v_melbankm，今天自己使用此函數時后面幾個參數不知道含義，翻了源文件看看，比較懶，沒翻譯成中文?？吹揭黄玫慕忉尯团cv_melcepst的比較博客請戳這里

函數解釋

v_melbankm determine matrix for a mel/erb/bark-spaced v_filterbank [X,MN,MX]=(P,N,FS,FL,FH,W)

Inputs:

p number of filters in v_filterbank or the filter spacing in k-mel/bark/erb [ceil(4.6*log10(fs))]

n length of fft

fs sample rate in Hz

fl low end of the lowest filter as a fraction of fs [default = 0]

fh high end of highest filter as a fraction of fs [default = 0.5]

w any sensible combination of the following:

‘b’ = bark scale instead of mel

‘e’ = erb-rate scale

‘l’ = log10 Hz frequency scale

‘f’ = linear frequency scale

‘c’ = fl/fh specify centre of low and high filters

‘h’ = fl/fh are in Hz instead of fractions of fs

‘H’ = fl/fh are in mel/erb/bark/log10

‘t’ = triangular shaped filters in mel/erb/bark domain (default)

‘n’ = hanning shaped filters in mel/erb/bark domain

‘m’ = hamming shaped filters in mel/erb/bark domain

‘z’ = highest and lowest filters taper down to zero [default]

‘y’ = lowest filter remains at 1 down to 0 frequency and highest filter remains at 1 up to nyquist freqency

‘u’ = scale filters to sum to unity

‘s’ = single-sided: do not double filters to account for negative frequencies

‘g’ = plot idealized filters [default if no output arguments present]

Note that the filter shape (triangular, hamming etc) is defined in the mel (or erb etc) domain.

Some people instead define an asymmetric triangular filter in the frequency domain.

If ‘ty’ or ‘ny’ is specified, the total power in the fft is preserved.

Outputs:

x a sparse matrix containing the v_filterbank amplitudes

If the mn and mx outputs are given then size(x)=[p,mx-mn+1]

otherwise size(x)=[p,1+floor(n/2)]

Note that the peak filter values equal 2 to account for the power

in the negative FFT frequencies.

mc the v_filterbank centre frequencies in mel/erb/bark

mn the lowest fft bin with a non-zero coefficient

mx the highest fft bin with a non-zero coefficient

Note: you must specify both or neither of mn and mx.

Examples of use:

(a) Calcuate the Mel-frequency Cepstral Coefficients

f=v_rfft(s); % v_rfft() returns only 1+floor(n/2) coefficients

x=v_melbankm(p,n,fs); % n is the fft length, p is the number of filters wanted

z=log(x*abs(f).^2); % multiply x by the power spectrum

c=dct(z); % take the DCT

(b) Calcuate the Mel-frequency Cepstral Coefficients efficiently

f=fft(s); % n is the fft length, p is the number of filters wanted

[x,mc,na,nb]=v_melbankm(p,n,fs); % na:nb gives the fft bins that are needed

z=log(x*(f(na:nb)).*conj(f(na:nb)));

? Plot the calculated filterbanks

plot((0:floor(n/2))*fs/n,melbankm(p,n,fs)') % fs=sample frequency

(d) Plot the idealized filterbanks (without output sampling)

v_melbankm(p,n,fs);

References:

[1] S. S. Stevens, J. Volkman, and E. B. Newman. A scale for the measurement

of the psychological magnitude of pitch. J. Acoust Soc Amer, 8: 185-19, 1937.

[2] S. Davis and P. Mermelstein. Comparison of parametric representations for

monosyllabic word recognition in continuously spoken sentences.

IEEE Trans Acoustics Speech and Signal Processing, 28 (4): 357-366, Aug. 1980.

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