filterbank(inp)

function [time_freq] = filterbank(inp)
%
% Simulation of an auditory perception model.
%
%  input: time sequence, continuous time, no windowing 
% output: time-frequency representation.
%
% Author: Yunbin Deng, work performed at Johns Hopkins Univeristy.
%         [e-mail] or [e-mail]
%
% Note: need to ran fb_para once to set the filterbank parameters
%       and then filterbank.m can be called in batch mode
%
% The algorithm was published in the following papers:
% 1.  "Analog Auditory Perception Model for Robust Speech Recognition", Y. Deng, S.
%      Chakrabartty, and G. Cauwenberghs, Proc. IEEE Int. Joint Conf. on Neural Network
%      (IJCNN), Budapest Hungary, 2004.
% 2.  "Analog Auditory Perception Model for Robust Speaker Recognition", Y. Deng, R. Xu,
%      IASTED, Signal and Image Processing, Honolulu, Hawaii, 2006.
%
% All rights reserved, free for academic education and non-profit research only.
%
% 

global bhd ahd;           % pre_amp
global bbd abd;           % bandpass
global bld ald ;          % lowpass
global bbd_last abd_last; % bandpass
global numChannel;

% setp 1: first order analog high pass filter
sig = filter(bhd,ahd,inp);

% step 2: N channel Mel/BARK-scale filter bank
for j = 1 : numChannel,
   y = filter(bbd(j,:),abd(j,:),sig);   % do it just once, twice almost does not help.

   % step 3: absolute value
   y = abs(y - mean(y)) ;

   % step 4: lowpass filter envelp extractor
   y = filter(bld(j,:), ald(j,:), y);  % does not help much

   % step 5: non-linear compression/bandpass
   y = log(y+0.0000001); % prevent log of zero
   y = filter(bbd_last(j,:),abd_last(j,:),y);

   % step 6:  decimation from 20khz to 100hz ( 10ms/feature frame)
   % time_freq(:,j) = y1(1:200:length(y1)); % for tidigit
   time_freq(:,j) = y(1:100:length(y)); % for yoho from 8khz to 80hz
end

% step 7:  dct, help to reduce dimension and improve about 1%
time_freq = dct(time_freq');
time_freq = time_freq(1:9,:);