Speech emotion recognition using a fuzzy approach

被引：9

作者：

Ton-That, An H. ^{[1
]}

Cao, Nhan T. ^{[2
]}

机构：

[1] Univ Finance & Mkt, Fac Informat Technol, Ho Chi Minh City, Vietnam

[2] Vietnam Natl Univ Ho Chi Minh City, Fac Informat Syst, Univ Informat Technol, Ho Chi Minh City, Vietnam

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2019年 / 36卷 / 02期

关键词：

Speech emotion recognition; fuzzy inference systems; fuzzy associative memory; pattern recognition; fuzzy approach; INFERENCE SYSTEMS;

D O I：

10.3233/JIFS-18594

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 introduces a fuzzy approach for classifying speech emotions in which a fuzzy inference system based on fuzzy associative memory (FAM-FIS) is used for recognizing speech emotions. Experiments on two databases of emotion speech Emo-DB in German and SAVEE in English, and feature of Mel-Frequency Cepstral Coefficients (MFCC) showed that the accuracy rates of the fuzzy inference system are better than that of Bayes and Support Vector Machine (SVM) on same kind of features and databases. Namely, with MFCC feature and 19 dimensions, Emo-DB is 74.31% and SAVEE is 97.29%.

引用

页码：1587 / 1597

页数：11

共 50 条

[1] Emotion recognition from speech signal using fuzzy clustering
Rovetta, Stefano
Mnasri, Zied
Masulli, Francesco
Cabri, Alberto
[J]. PROCEEDINGS OF THE 11TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT 2019), 2019, 1 : 120 - 127
[2] Fuzzy emotion recognition in natural speech dialogue
Austermann, A
Esau, N
Kleinjohann, L
Kleinjohann, B
[J]. 2005 IEEE INTERNATIONAL WORKSHOP ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (RO-MAN), 2005, : 317 - 322
[3] Emotion Statuses Recognition of Speech Signal Using Intuitionistic Fuzzy Set
Yang, Taoxiang
Yang, Jian
Bi, FuKun
[J]. 2009 WRI WORLD CONGRESS ON SOFTWARE ENGINEERING, VOL 1, PROCEEDINGS, 2009, : 204 - +
[4] Distinctive Approach for Speech Emotion Recognition Using Machine Learning
Singh, Yogyata
Neetu
Rani, Shikha
[J]. MACHINE LEARNING, IMAGE PROCESSING, NETWORK SECURITY AND DATA SCIENCES, MIND 2022, PT I, 2022, 1762 : 39 - 51
[5] Bimodal Approach in Emotion Recognition using Speech and Facial Expressions
Emerich, Simina
Lupu, Eugen
Apatean, Anca
[J]. ISSCS 2009: INTERNATIONAL SYMPOSIUM ON SIGNALS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS,, 2009, : 297 - 300
[6] Emotion Recognition using Imperfect Speech Recognition
Metze, Florian
Batliner, Anton
Eyben, Florian
Polzehl, Tim
Schuller, Bjoern
Steidl, Stefan
[J]. 11TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2010 (INTERSPEECH 2010), VOLS 1-2, 2010, : 478 - +
[7] A Fuzzy Approach for Facial Emotion Recognition
Farahani, Fatemeh Shahrabi
Sheikhan, Mansour
Farrokhi, Ali
[J]. 2013 13TH IRANIAN CONFERENCE ON FUZZY SYSTEMS (IFSC), 2013,
[8] Fuzzy speech emotion recognition considering semantic awareness
Xiong, Yu
Cai, Ting
Zhong, Xin
Zhou, Song
Cai, Linqin
[J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (03) : 7367 - 7377
[9] Speech Emotion Recognition using DWT
Lalitha, S.
Mudupu, Anoop
Nandyala, Bala Visali
Munagala, Renuka
[J]. 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2015, : 20 - 23
[10] Speech Emotion Recognition Using CNN
Huang, Zhengwei
Dong, Ming
Mao, Qirong
Zhan, Yongzhao
[J]. PROCEEDINGS OF THE 2014 ACM CONFERENCE ON MULTIMEDIA (MM'14), 2014, : 801 - 804

← 1 2 3 4 5 →