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score2Word.m
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score2Word.m
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% Code written by Tao Wang (http://cs.stanford.edu/people/twangcat/)
% given sliding window classifier scores, predict the word label using
% a Viterbi-style alignment algorithm.
function[predword, bestdist, matchScore, bounds] = score2Word(scores, LEX)
[conf pred_y] = max(scores,[],1);
if length(conf)>500
predword = ''; bestdist = 0; matchScore = -10; bounds = [1,length(conf)];
return;
end
chars = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789';
case_insen_scores = [max(scores(1:26,:), scores(27:52,:)); max(scores(1:26,:), scores(27:52,:)); scores(53:62,:) ]; %make scores case-insensitive
[dummy, good_idx, margin] = filterScores(scores,2, -100);
rawWord = chars(pred_y(good_idx));
lexicon = LEX;
s = length(good_idx);
matchScoreArray = -99*ones(1,length(lexicon));
for i = 1:length(lexicon)
lexiconword = regexprep(char(lexicon{i}),'[^a-zA-Z0-9]','');
if length(lexiconword)>2 && length(lexiconword)<16
[tempscore real_good_idx]= getMatchScore(case_insen_scores,lexiconword, good_idx);
matchScoreArray(i) = tempscore;
%disp([lexiconword ' ' num2str(tempscore)])
end
end
[matchScore, idx] = max(matchScoreArray);
bestword = regexprep(char(lexicon{idx}),'[^a-zA-Z0-9]','');
[tempscore real_good_idx]= getMatchScore(case_insen_scores,bestword, good_idx);
bounds = [max(1, real_good_idx(1)-8), size(scores,2) - min(size(scores,2), real_good_idx(end)+8)]; %bounds(1) is the dist from 1st char to left margin, bounds(2) is the dist from last char to right margin
predword=upper(regexprep(char(lexicon{idx}),'[^a-zA-Z0-9]',''));
if isempty(predword)
matchScore = 0;
end
bestdist = 0;