Wrong valence and arousal

[bmond]

I have tested with different kind of files where emotions are angry happy sad or calm. I am supposed to get valence and arousal values in such a way that 1st quadrant means excited/happy || 2nd quadrant means angry || 3rd quadrant means sad || 4th quadrant means calm. However for every expression I am getting same quadrant only and that is 1st. Am I doing something wrong? Do I need to train first with some data for better result or do I need to do noise filtering beforehand?

The result I am getting where arousal and valence as:
angry1
arousal:
0.158374
valence:
0.530165

Angry2
arousal:
0.155097
valence:
0.163162

Calm
arousal:
0.228325
valence:
0.144437

Happy1
arousal:
0.175005
valence:
0.350349

Happy2
arousal:
0.248143
valence:
0.200598

Sad1
arousal:
0.144986
valence:
0.358285

Sad2
arousal:
0.276521
valence:
0.342779

audioAnalytics.zip

[hesamsagha]

Hi bmond,
The problem is the mismatched data distribution. The model has been trained on the RECOLA database (https://diuf.unifr.ch/diva/recola/). For more detail, see the paper: (https://www.isca-speech.org/archive/Interspeech_2016/pdfs/1124.PDF).
You may retrain a new classifier for your problem. See the guidance here: (https://github.com/openXBOW/openXBOW).
I hope it helps.