Preliminary Arabic Speech Emotion Classification

被引:0
作者
Meftah, Ali [1 ]
Selouani, Sid-Ahmed [2 ]
Alotaibi, Yousef A. [1 ]
机构
[1] King Saud Univ, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
[2] Univ Moncton, Shippegan, NB E8S 1P6, Canada
来源
2014 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT) | 2014年
关键词
Emotion; Arabic; Classifier; Recognition;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, the acoustic features of pitch, intensity, formants, and speech rate are extracted and used to classify the following Arabic speech emotions: neutral, sad, happy, surprised, and angry. Three sentences spoken by four male and four female native Arabic speakers were selected from a newly developed Arabic speech corpus (KSUEmotions). Perception tests using human listeners yielded scores of 87% (male speakers), 84% (female speakers), and 85% (both male and female) accuracy. The best results for the emotion recognition performance were 83%, 56%, and 78% for male, female, and both together, respectively. Anger was the most readily recognized emotion, while happiness was the most challenging to identify. Pitch and intensity features are key in recognizing the Arabic speech emotion of anger.
引用
收藏
页码:179 / 182
页数:4
相关论文
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