www.pudn.com > VAD-DTW-HMM.rar > viterbi.m

function [prob,q] = viterbi(hmm, O) 
%Viterbi算法 
%输入: 
%  hmm -- hmm模型 
%  O   -- 输入观察序列, N*D, N为帧数,D为向量维数 
%输出: 
%  prob -- 输出概率 
%  q    -- 状态序列 
 
init  = hmm.init;	%初始概率 
trans = hmm.trans;	%转移概率 
mix   = hmm.mix;	%高斯混合 
N     = hmm.N;		%HMM状态数 
T     = size(O,1);	%语音帧数 
 
% 计算log(init); 
ind1  = find(init>0); 
ind0  = find(init<=0); 
init(ind0) = -inf; 
init(ind1) = log(init(ind1)); 
 
% 计算log(trans); 
ind1 = find(trans>0); 
ind0 = find(trans<=0); 
trans(ind0) = -inf; 
trans(ind1) = log(trans(ind1)); 
 
% 初始化 
delta = zeros(T,N); 
fai   = zeros(T,N); 
q     = zeros(T,1); 
 
% t=1 
x = O(1,:); 
for i = 1:N 
	delta(1,i) = init(i) + log(mixture(mix(i),x)); 
end 
 
% t=2:T 
for t = 2:T 
for j = 1:N 
	[delta(t,j) fai(t,j)] = max(delta(t-1,:) + trans(:,j)'); 
	x = O(t,:); 
	delta(t,j) = delta(t,j) + log(mixture(mix(j),x)); 
end 
end 
 
% 最终概率和最后节点 
[prob q(T)] = max(delta(T,:)); 
 
% 回溯最佳状态路径 
for t=T-1:-1:1 
	q(t) = fai(t+1,q(t+1)); 
end