Audio-visual emotion recognition based on a deep convolutional neural network

Kh. Aghajani

Volume 10, Issue 4 , November 2022, , Pages 529-537

https://doi.org/10.22044/jadm.2022.11809.2331

Abstract
  Emotion recognition has several applications in various fields, including human-computer interactions. In recent years, various methods have been proposed to recognize emotion using facial or speech information. While the fusion of these two has been paid less attention in emotion recognition. In this ...  Read More

Speech Emotion Recognition using Enriched Spectrogram and Deep Convolutional Neural Network Transfer Learning

B. Z. Mansouri; H.R. Ghaffary; A. Harimi

Volume 10, Issue 4 , November 2022, , Pages 539-547

https://doi.org/10.22044/jadm.2022.12241.2372

Abstract
  Speech emotion recognition (SER) is a challenging field of research that has attracted attention during the last two decades. Feature extraction has been reported as the most challenging issue in SER systems. Deep neural networks could partially solve this problem in some other applications. In order ...  Read More

Multi-Task Feature Selection for Speech Emotion Recognition: Common Speaker-Independent Features Among Emotions

E. Kalhor; B. Bakhtiari

Volume 9, Issue 3 , July 2021, , Pages 269-282

https://doi.org/10.22044/jadm.2021.9800.2118

Abstract
  Feature selection is the one of the most important steps in designing speech emotion recognition systems. Because there is uncertainty as to which speech feature is related to which emotion, many features must be taken into account and, for this purpose, identifying the most discriminative features is ...  Read More

Classification of emotional speech using spectral pattern features

Ali Harimi; Ali Shahzadi; Alireza Ahmadyfard; Khashayar Yaghmaie

Volume 2, Issue 1 , March 2014, , Pages 53-61

https://doi.org/10.22044/jadm.2014.150

Abstract
  Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic ...  Read More