Emotion Recognition Using Neural Networks

被引：0
|
作者：
Unluturk, Mehmet S. [1 ]
Oguz, Kaya [1 ]
Atay, Coskun [1 ]
机构：
[1] Izmir Univ Econ, Dept Software Engn, TR-35330 Izmir, Turkey
来源：
NN'09: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON NEURAL NETWORKS | 2009年
关键词：
Back propagation learning algorithm; Neural network; Emotion; Speech; Power Spectrum; Fast-Fourier Transform (FFT);
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：
Speech and emotion recognition improve the quality of human computer interaction and allow more easy to use interfaces for every level of user in software applications. In this study, we have developed the emotion recognition neural network (ERNN) to classify the voice signals for emotion recognition. The ERNN has 128 input nodes, 20 hidden neurons, and three summing Output nodes. A set of 97932 training sets is used to train the ERNN. A new set of 24483 testing sets is utilized to test the EPNN performance. The samples tested for voice recognition are acquired from the movies "Anger Management" and "Pick of Destiny". ERNN achieves an average recognition performance of 100%. This high level of recognition suggests that the ERNN is a promising method for emotion recognition in computer applications.
引用
收藏
页码：82 / 85
页数：4
相关论文
共 50 条
  • [1] Emotion recognition in speech using neural networks
    Nicholson, J
    Takahashi, K
    Nakatsu, R
    AFFECTIVE MINDS, 2000, : 215 - 220
  • [2] Emotion recognition in speech using neural networks
    Nicholson, J
    Takahashi, K
    Nakatsu, R
    NEURAL COMPUTING & APPLICATIONS, 2000, 9 (04): : 290 - 296
  • [3] Emotion Recognition in Speech Using Neural Networks
    J. Nicholson
    K. Takahashi
    R. Nakatsu
    Neural Computing & Applications, 2000, 9 : 290 - 296
  • [4] Facial emotion recognition using neural networks
    Ahmad, Faizaan
    Ahmad, Amreen
    Verma, Vijay Kumar
    JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, 2023, 44 (06): : 1115 - 1126
  • [5] Facial Emotion Recognition using Convolutional Neural Networks
    Rzayeva, Zeynab
    Alasgarov, Emin
    2019 IEEE 13TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT 2019), 2019, : 91 - 95
  • [6] Facial Emotion Recognition Using Residual Neural Networks
    Kirbiz, Serap
    ELECTRICA, 2024, 24 (03): : 818 - 825
  • [7] Speech emotion recognition using spiking neural networks
    Buscicchio, Cosimo A.
    Gorecki, Przemyslaw
    Caponetti, Laura
    FOUNDATIONS OF INTELLIGENT SYSTEMS, PROCEEDINGS, 2006, 4203 : 38 - 46
  • [8] Facial Emotion Recognition using Convolutional Neural Networks
    Gopichand, G.
    Reddy, I. Ravi Prakash
    Santhi, H.
    Akula, Vijaya Krishna
    IMPENDING INQUISITIONS IN HUMANITIES AND SCIENCES, ICIIHS-2022, 2024, : 198 - 203
  • [9] Emotion Recognition Using Pretrained Deep Neural Networks
    Dobes, Marek
    Sabolova, Natalia
    ACTA POLYTECHNICA HUNGARICA, 2023, 20 (04) : 195 - 204
  • [10] Visual Emotion Recognition Using Deep Neural Networks
    Iliev, Alexander I.
    Mote, Ameya
    DIGITAL PRESENTATION AND PRESERVATION OF CULTURAL AND SCIENTIFIC HERITAGE, 2022, 12 : 77 - 88
12345