UNIZA System for the „Emotion in Music“ task

at MediaEval 2015

Ing.  Miroslav  Malík  Department  of  Telecommunica1ons  and  Mul1media  Faculty  of  Electrical  Engineering  University  of  Žilina,  Slovakia  

UNIZA  system      

1  

Par9cle  Swamp    Op9miza9on  /  Gene9c  Algorithm    

•  Parallel  run  of  PSO  /  GA  

•  Best  individuals  from  both  algorithms  selected  into  next  itera1on  of  the  op1miza1on  process  

•  fitness  func1on  -­‐  RMSE  between  predicted  and  ground  truth  labels  

2  

Audio  Features  

•  Op1mal  features  from  baseline  set  •  Features  from  MIR  Toolbox  

•  2  best  combina1ons  used:  – Op#mal_1  –  139  features  – Op#mal_2  –  129  features  – 72  iden1cal  features  (MFCC,  slope,  skewness...)  

3  

Results  of  our  system  on  the  development  data  

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5  

Official  results  

•  (almost)  equal  result  obtained  using  only  approximately  50%  of  the  baseline  features  

•  it  might  be  useful  to  apply  the  SVR  with  different  kernel  parameters  and/or  also  different  feature  sets  for  each  emo1onal  dimension  

6  

Conclusion    and  future  work  

THANK  YOU  FOR  YOUR  ATTENTION