gusucode.com > 《MATLAB图像与视频处理实用案例详解》代码 > 《MATLAB图像与视频处理实用案例详解》代码/第 19 章 基于语音识别的信号灯图像模拟控制技术/voicebox/distchar.m
function d=distchar(ar1,ar2,mode) %DISTCHAR calculates the cosh spectral distance between AR coefficients D=(AR1,AR2,MODE) % % Inputs: AR1,AR2 AR coefficient sets to be compared. Each row contains a set of coefficients. % AR1 and AR2 must have the same number of columns. % % MODE Character string selecting the following options: % 'x' Calculate the full distance matrix from every row of AR1 to every row of AR2 % 'd' Calculate only the distance between corresponding rows of AR1 and AR2 % The default is 'd' if AR1 and AR2 have the same number of rows otherwise 'x'. % % Output: D If MODE='d' then D is a column vector with the same number of rows as the shorter of AR1 and AR2. % If MODE='x' then D is a matrix with the same number of rows as AR1 and the same number of columns as AR2'. % % The COSH spectral distance is the average over +ve and -ve frequency of % % cosh(log(p1/p2))-1 = (p1-p2)^2/(2p1*p2) = (p1/p2 + p2/p1)/2 - 1 % % Where p1 and p2 are the power spectra corresponding to the AR coefficient sets AR1 and AR2. % The COSH distance is a symmetrical version of the Itakura-Saito distance: distchar(x,y)=(distisar(x,y)+distisar(y,x))/2 % Since the power spectrum is the fourier transform of the autocorrelation, we can calculate % the average value of p1/p2 by taking the 0'th order term of the convolution of the autocorrelation % functions associated with p1 and 1/p2. Since 1/p2 corresponds to an FIR filter, this convolution is % a finite sum even though the autocorrelation function of p1 is infinite in extent. % The Cosh distance can also be calculated directly from the power spectra; providing np is large % enough, the values of d0 and d1 in the following will be very similar: % % np=255; d0=distchar(ar1,ar2); d1=distchpf(lpcar2pf(ar1,np),lpcar2pf(ar2,np)) % % Ref: A.H.Gray Jr and J.D.Markel, "Distance measures for speech processing", IEEE ASSP-24(5): 380-391, Oct 1976 % L. Rabiner abd B-H Juang, "Fundamentals of Speech Recognition", Section 4.5, Prentice-Hall 1993, ISBN 0-13-015157-2 % Copyright (C) Mike Brookes 1997 % Version: $Id: distchar.m,v 1.4 2007/05/04 07:01:38 dmb Exp $ % % VOICEBOX is a MATLAB toolbox for speech processing. % Home page: http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/voicebox.html % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % This program is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation; either version 2 of the License, or % (at your option) any later version. % % This program is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You can obtain a copy of the GNU General Public License from % http://www.gnu.org/copyleft/gpl.html or by writing to % Free Software Foundation, Inc.,675 Mass Ave, Cambridge, MA 02139, USA. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% [nf1,p1]=size(ar1); nf2=size(ar2,1); p2=p1+1; m1=zeros(nf1,2*p1); m2=zeros(nf2,2*p1); m1(:,1:p1)=lpcar2rr(ar1); m1(:,p2:end)=lpcar2ra(ar1); m1(:,1)=m1(:,1)*0.5; m1(:,p2)=m1(:,p1+1)*0.5; m2(:,p2:end)=lpcar2rr(ar2); m2(:,1:p1)=lpcar2ra(ar2); if nargin<3 | isempty(mode) mode='0'; end if any(mode=='d') | (mode~='x' & nf1==nf2) nx=min(nf1,nf2); d=sum(m1(1:nx,:).*m2(1:nx,:),2)-1; else d=m1*m2'-1; end