A systematic review on affective computing: Emotion models, databases, and recent advances

Y Wang, W Song, W Tao, A Liotta, D Yang, X Li, S Gao… - Information …, 2022 - Elsevier
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

A comprehensive review of speech emotion recognition systems

TM Wani, TS Gunawan, SAA Qadri, M Kartiwi… - IEEE …, 2021 - ieeexplore.ieee.org
During the last decade, Speech Emotion Recognition (SER) has emerged as an integral
component within Human-computer Interaction (HCI) and other high-end speech processing …

Speech emotion recognition with deep convolutional neural networks

D Issa, MF Demirci, A Yazici - Biomedical Signal Processing and Control, 2020 - Elsevier
The speech emotion recognition (or, classification) is one of the most challenging topics in
data science. In this work, we introduce a new architecture, which extracts mel-frequency …

Deep learning based multimodal emotion recognition using model-level fusion of audio–visual modalities

AI Middya, B Nag, S Roy - Knowledge-Based Systems, 2022 - Elsevier
Emotion identification based on multimodal data (eg, audio, video, text, etc.) is one of the
most demanding and important research fields, with various uses. In this context, this …

Ifogsim2: An extended ifogsim simulator for mobility, clustering, and microservice management in edge and fog computing environments

R Mahmud, S Pallewatta, M Goudarzi… - Journal of Systems and …, 2022 - Elsevier
Abstract Internet of Things (IoT) has already proven to be the building block for next-
generation Cyber–Physical Systems (CPSs). The considerable amount of data generated by …

Speech emotion recognition enhanced traffic efficiency solution for autonomous vehicles in a 5G-enabled space–air–ground integrated intelligent transportation …

L Tan, K Yu, L Lin, X Cheng… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Speech emotion recognition (SER) is becoming the main human–computer interaction logic
for autonomous vehicles in the next generation of intelligent transportation systems (ITSs). It …

MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach

S Kwon - Expert Systems with Applications, 2021 - Elsevier
Speech is the most dominant source of communication among humans, and it is an efficient
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …

[HTML][HTML] Survey on bimodal speech emotion recognition from acoustic and linguistic information fusion

BT Atmaja, A Sasou, M Akagi - Speech Communication, 2022 - Elsevier
Speech emotion recognition (SER) is traditionally performed using merely acoustic
information. Acoustic features, commonly are extracted per frame, are mapped into emotion …

An ensemble 1D-CNN-LSTM-GRU model with data augmentation for speech emotion recognition

MR Ahmed, S Islam, AKMM Islam… - Expert Systems with …, 2023 - Elsevier
Precise recognition of emotion from speech signals aids in enhancing human–computer
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …

Learning alignment for multimodal emotion recognition from speech

H Xu, H Zhang, K Han, Y Wang, Y Peng, X Li - arXiv preprint arXiv …, 2019 - arxiv.org
Speech emotion recognition is a challenging problem because human convey emotions in
subtle and complex ways. For emotion recognition on human speech, one can either extract …