A Neural Network Based Approach for Recognition of Basic Emotions from Speech

被引：0

作者：

Sham-E-Ansari, Md ^{[1
]}

Disha, Shaminaj Towfika ^{[1
]}

Chowdhury, Atiqul Islam ^{[2
]}

Hasan, Md Khairul ^{[1
]}

机构：

[1] Ahsanullah Univ Sci & Technol, Dept Comp Sci & Engn, Dhaka, Bangladesh

[2] United Int Univ, Dept Comp Sci & Engn, Dhaka, Bangladesh

来源：

2020 IEEE REGION 10 SYMPOSIUM (TENSYMP) - TECHNOLOGY FOR IMPACTFUL SUSTAINABLE DEVELOPMENT | 2020年

关键词：

Speech Emotion; MFCC; Neural Network; MLP Classifier;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Recognition of emotions from the speech is one of the most researched topics now a days in the field of signal processing and human machine interaction system. Unlike humans, machines have a lacking ability to perceive and show emotions. However, human-computer interaction can be improved with emotions recognition automation system by reducing the need for human access. In this research paper, a method for speech emotion recognition is presented using Neural Network (NN) with Mel Frequency Cepstral Coefficients (MFCC) features. Berlin Emotional Speech dataset (EmoDB) is used here for classification purposes. From our research, we have found an average of 73.40% accuracy with the highest accuracy of 82.35%.

引用

页码：807 / 810

页数：4

共 50 条

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