Mendeley
TY  _  JOUR
ID  -  139511231511464967
TI  -  Speech Emotion Recognition Based on Fusion Method
JO  -  Journal of Information Systems and Telecommunication (JIST) 
JA  -  ES
LA  -  en
SN  -  2322-1437
AU  -  معتمد سارا
AU  -  Setayeshi Saeed
AU  -  Rabiee Azam
AU  -  شریفی آرش
AD  -  استادیار، گروه کامپیوتر، واحد فومن و شفت، دانشگاه آزاد اسلامی واحد، فومن، ایران
AD  -  Amirkabir
AD  -  Islamic Azad University Isfahan
AD  -  گروه مهندسی کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
Y1  -  2017
PY  -  2017
VL  -  17
IS  -  5
SP  -  1
EP  -  10
KW  -  Speech Emotion Recognition

KW  -   Mel Frequency Cepstral Coefficient (MFCC)

KW  -   Fixed and Variable Structures Stochastic Automata

KW  -  Multi-constraint
KW  -   Fusion Method
DO  -  
N2  -  Speech emotion signals are the quickest and most neutral method in individuals’ relationships, leading researchers to develop speech emotion signal as a quick and efficient technique to communicate between man and machine. This paper introduces a new classification method using multi-constraints partitioning approach on emotional speech signals. To classify the rate of speech emotion signals, the features vectors are extracted using Mel frequency Cepstrum coefficient (MFCC) and auto correlation function coefficient (ACFC) and a combination of these two models. This study found the way that features’ number and fusion method can impress in the rate of emotional speech recognition. The proposed model has been compared with MLP model of recognition. Results revealed that the proposed algorithm has a powerful capability to identify and explore human emotion. 
UR  - rimag.ir/fa/Article/15013
L1  - rimag.ir/fa/Article/Download/15013
ER  -  
