speech emotion recognition based on fusion method
سال انتشار: 1395
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 833
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شناسه ملی سند علمی:
JR_JIST-5-1_008
تاریخ نمایه سازی: 7 شهریور 1396
چکیده مقاله:
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
کلیدواژه ها:
Speech Emotion Recognition ، Mel Frequency Cepstral Coefficient (MFCC) ، Fixed and Variable Structures Stochastic Automata ، Multi-constraint ، Fusion Method
نویسندگان
Sara Motamed
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Saeed Setayeshi
Department of Medical Radiation, Amirkabir University of Technology, Tehran, Iran
Azam Rabiee
Department of Computer Science, Dolatabad Branch, Islamic Azad University, Isfahan, Iran
Arash Sharifi
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran