Speech Emotion Recognition Based on Arabic Features

被引：0

作者：

Meddeb, Mohamed ^{[1
]}

Karray, Hichem ^{[1
]}

Alimi, Adel M. ^{[1
]}

机构：

[1] Ecole Natl Ingenieurs Sfax, Res Grp Intelligent Machines, Sfax, Tunisia

来源：

2015 15TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA) | 2015年

关键词：

Speech; Arabic; multi class classifier; response time; SYMs; descriptors; culture;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents the principal phase of extraction and recognition of the basic emotions in the Arabic speech applied to jive emotional states were taken into effect; neutral, sadness, fear, anger and happiness. Emotional speech database REGIM_TES[1] was created and evaluated to provide all practical experiences of extraction. The selected descriptors in our study are; Pitch of voice, Energy, MFCCs, Formant, LPC and the spectrogram. Descriptors showed the importance of the Arabic language on the physiological events and the influence of culture on emotional behavior. A comparative study between the kernel functions has enabled us to promote the RBF kernel SVMs multiclass classifier [15] performing the classification phase.

引用

页码：46 / 51

页数：6

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