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   speech emotion recognition based on fusion method  
   
نویسنده motamed sara ,setayeshi saeed ,rabiee azam ,sharifi arash
منبع journal of information systems and telecommunication - 2017 - دوره : 5 - شماره : 1 - صفحه:50 -56
چکیده    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 multiconstraints 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 speech emotion recognition; mel frequency cepstral coefficient (mfcc); fixed and variable structures stochastic automata; multi-constraint; fusion method.
آدرس islamic azad university, science and research branch, department of computer engineering, ایران, amirkabir university of technology, department of medical radiation, ایران, islamic azad university, dolatabad branch, department of computer science, ایران, islamic azad university, science and research branch, department of computer engineering, ایران
پست الکترونیکی a.sharifi@srbiau.ac.ir
 
     
   
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