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Speech-based emotion classification using multiclass SVM with hybrid kernel and thresholding fusion

Autor
Yang, N.; Muraleedharan, R.; Khol, J.; Demirkol, I.; Heinzelman, W.; Sturge-Apple, M.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
2012 IEEE Workshop on Spoken Language Technology
Any de l'edició
2012
Data de presentació
2012-12
Llibre d'actes
2012 IEEE Workshop on Spoken Language Technology: SLT 2012: proceedings: December 2-5, 2012: Miami, Florida, USA
Pàgina inicial
455
Pàgina final
460
DOI
https://doi.org/10.1109/SLT.2012.6424267 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/22610 Obrir en finestra nova
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6424267&queryText%3DSpeech-based+emotion+classification+using+multiclass+SVM+with+hybrid+kernel+and+thresholding+fusion Obrir en finestra nova
Resum
Emotion classification is essential for understanding human interactions and hence is a vital component of behavioral studies. Although numerous algorithms have been developed, the emotion classification accuracy is still short of what is desired for the algorithms to be used in real systems. In this paper, we evaluate an approach where basic acoustic features are extracted from speech samples, and the One-Against-All (OAA) Support Vector Machine (SVM) learning algorithm is used. We use a novel ...
Citació
Yang, N. [et al.]. Speech-based emotion classification using multiclass SVM with hybrid kernel and thresholding fusion. A: IEEE Workshop on Spoken Language Technology. "2012 IEEE Workshop on Spoken Language Technology: SLT 2012: proceedings: December 2-5, 2012: Miami, Florida, USA". Miami, FL: 2012, p. 455-460.
Paraules clau
Emotion classification, Hybrid kernel, Speaker independent, Support vector machine, Thresholding fusion
Grup de recerca
WNG - Grup de xarxes sense fils

Participants

  • Yang, N.  (autor ponent)
  • Muraleedharan, Rajani  (autor ponent)
  • Khol, J.  (autor ponent)
  • Demirkol, Ilker Seyfettin  (autor ponent)
  • Heinzelman, Wendi  (autor ponent)
  • Sturge Apple, Melissa L.  (autor ponent)