loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Third International Conference on Information Technology and Applications (ICITA'05) Volume 1
Comparison between Fuzzy and NN Method for Speech Emotion Recognition
Sydney, Australia
July 04-July 07
ISBN: 0-7695-2316-1
Aishah Abdul Razak, Multimedia University
Ryoichi Komiya, Multimedia University
Mohamad Izani Zainal Abidin, Multimedia University
This paper discusses an approach towards automatic recognition of emotion in speech which is adopted into a system named Voice Driven Emotion Recognizer Mobile Phone (VDERM). First, a design for the emotion recognizer is proposed. LPC analysis algorithm has been used for the speech emotion feature extraction. A total of 18 speech features have been selected to represent each emotion. A database consisting of emotional Malay and English, male and female voice samples have been developed for training and recognition purposes. Two recognition methods namely neural network and fuzzy model have been experimented and compared. The results show that both methods have their own advantage and disadvantage in application to emotion recognition. A recognition rate of up 60% is achievable by using these computer methods which is sufficient based on the recognition rate achieved by human.
Index Terms:
emotion recognition speech processing, feature extraction, neural network, fuzzy model
Citation:
Aishah Abdul Razak, Ryoichi Komiya, Mohamad Izani Zainal Abidin, "Comparison between Fuzzy and NN Method for Speech Emotion Recognition," icita, vol. 1, pp.297-302, Third International Conference on Information Technology and Applications (ICITA'05) Volume 1, 2005
Usage of this product signifies your acceptance of the Terms of Use.