A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
Speech emotion recognition: a comprehensive survey
MJ Al-Dujaili, A Ebrahimi-Moghadam - Wireless Personal Communications, 2023 - Springer
Speech emotion recognition could be considered a new topic in speech processing where
he plays that plays an essential role in human interaction. Emotions are a king of speech …
he plays that plays an essential role in human interaction. Emotions are a king of speech …
Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals
Depression stands as one of the most widespread psychological disorders and has
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
Impact of feature selection algorithm on speech emotion recognition using deep convolutional neural network
Speech emotion recognition (SER) plays a significant role in human–machine interaction.
Emotion recognition from speech and its precise classification is a challenging task because …
Emotion recognition from speech and its precise classification is a challenging task because …
Improving speech emotion recognition with adversarial data augmentation network
L Yi, MW Mak - IEEE transactions on neural networks and …, 2020 - ieeexplore.ieee.org
When training data are scarce, it is challenging to train a deep neural network without
causing the overfitting problem. For overcoming this challenge, this article proposes a new …
causing the overfitting problem. For overcoming this challenge, this article proposes a new …
Exploring deep spectrum representations via attention-based recurrent and convolutional neural networks for speech emotion recognition
The automatic detection of an emotional state from human speech, which plays a crucial role
in the area of human-machine interaction, has consistently been shown to be a difficult task …
in the area of human-machine interaction, has consistently been shown to be a difficult task …
Learning deep multimodal affective features for spontaneous speech emotion recognition
S Zhang, X Tao, Y Chuang, X Zhao - Speech Communication, 2021 - Elsevier
Recently, spontaneous speech emotion recognition has become an active and challenging
research subject. This paper proposes a new method of spontaneous speech emotion …
research subject. This paper proposes a new method of spontaneous speech emotion …
Emonet: A transfer learning framework for multi-corpus speech emotion recognition
In this manuscript, the topic of multi-corpus Speech Emotion Recognition (SER) is
approached from a deep transfer learning perspective. A large corpus of emotional speech …
approached from a deep transfer learning perspective. A large corpus of emotional speech …
Speech emotion recognition based on formant characteristics feature extraction and phoneme type convergence
Abstract Speech Emotion Recognition (SER) has numerous applications including human-
robot interaction, online gaming, and health care assistance. While deep learning-based …
robot interaction, online gaming, and health care assistance. While deep learning-based …
Bangla speech emotion recognition and cross-lingual study using deep CNN and BLSTM networks
S Sultana, MZ Iqbal, MR Selim, MM Rashid… - IEEE …, 2021 - ieeexplore.ieee.org
In this study, we have presented a deep learning-based implementation for speech emotion
recognition (SER). The system combines a deep convolutional neural network (DCNN) and …
recognition (SER). The system combines a deep convolutional neural network (DCNN) and …