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
Link To Document :
بازگشت