Mercurial > hg > emotion-detection-top-level
view Code/Collation/basicMetricSet.m @ 4:92ca03a8fa99 tip
Update to ICASSP 2013 benchmark
author | Dawn Black |
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date | Wed, 13 Feb 2013 11:02:39 +0000 |
parents | e1cfa7765647 |
children |
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function [metrics] = basicMetricSet( frameByFrameMetric, statsFileID ) % from ShahHewlitt2008 metrics = []; meanValue = mean( frameByFrameMetric ); metrics = [metrics meanValue]; fprintf( statsFileID, ' %f ', meanValue ); % median (not from ShahHewlitt2008) % medianValue = median( frameByFrameMetric ); % metrics = [metrics medianValue]; % fprintf( statsFileID, ' %f ', medianValue ); % % Standard deviation % stdValue = std( frameByFrameMetric ); % metrics = [metrics stdValue]; % fprintf( statsFileID, '\t %f ', stdValue ); % the varience seemed to make the pitch calculations worse, but I'm not % sure I am using it correctly - Dawn % Variance varValue = var(frameByFrameMetric); metrics = [metrics varValue]; fprintf( statsFileID, ' %f ', varValue ); % Minimum minValue = min( frameByFrameMetric ); metrics = [metrics minValue]; fprintf( statsFileID, ' %f ', minValue ); % Maximum maxValue = max( frameByFrameMetric ); metrics = [metrics maxValue]; fprintf( statsFileID, ' %f ', maxValue ); % range (not from ShahHewlitt2008) % rangeValue = max( frameByFrameMetric ) - min( frameByFrameMetric ); % metrics = [metrics rangeValue]; % fprintf( statsFileID, ' %f ', rangeValue ); end