• DocumentCode
    3446039
  • Title

    Classifier fusion for speech emotion recognition

  • Author

    Fu, Liqin ; Wang, Changjiang ; Zhang, Yongmei

  • Author_Institution
    Nat. Key Lab. for Electron. Meas. Technol., North Univ. of China, Taiyuan, China
  • Volume
    3
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    407
  • Lastpage
    410
  • Abstract
    According to multidimensional emotion space model, an improved queuing voting algorithm was proposed to implement the fusion among multiple emotion classifiers for a good emotion recognition result. Firstly, three kinds of classifier were designed based on hidden Markov model (HMM) and artificial neural network (ANN). Then, the improved queuing voting algorithm was used to fuse them. Experimental study had been carried out using Beihang University mandarin emotion speech database and Berlin database of emotional speech respectively. The results proved that the improved queuing voting algorithm can attain better fusion effect than conventional fusion algorithm and excel any single classifier evidently.
  • Keywords
    emotion recognition; hidden Markov models; neural nets; pattern classification; queueing theory; speech recognition; Beihang University; Berlin database; Mandarin emotion speech database; artificial neural network; classifier fusion; hidden Markov model; improved queuing voting algorithm; speech emotion recognition; Artificial neural networks; Databases; Hidden Markov models; Speech; ANN; HMM; classifier fusion; emotion recognition; voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658619
  • Filename
    5658619