Emotion recognition using different sensors, emotion models, methods and datasets: A comprehensive review
Y Cai, X Li, J Li - Sensors, 2023 - mdpi.com
In recent years, the rapid development of sensors and information technology has made it
possible for machines to recognize and analyze human emotions. Emotion recognition is an …
possible for machines to recognize and analyze human emotions. Emotion recognition is an …
Big educational data & analytics: Survey, architecture and challenges
KLM Ang, FL Ge, KP Seng - IEEE access, 2020 - ieeexplore.ieee.org
The proliferation of mobile devices and the rapid development of information and
communication technologies (ICT) have seen increasingly large volume and variety of data …
communication technologies (ICT) have seen increasingly large volume and variety of data …
A low-rank matching attention based cross-modal feature fusion method for conversational emotion recognition
Conversational emotion recognition (CER) is an important research topic in human-
computer interactions. Although recent advancements in transformer-based cross-modal …
computer interactions. Although recent advancements in transformer-based cross-modal …
Audio-visual emotion recognition in video clips
This paper presents a multimodal emotion recognition system, which is based on the
analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral …
analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral …
K-Means Clustering-Based Kernel Canonical Correlation Analysis for Multimodal Emotion Recognition in Human–Robot Interaction
L Chen, K Wang, M Li, M Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this article, K-meansclustering-based Kernel canonical correlation analysis algorithm is
proposed for multimodal emotion recognition in human–robot interaction (HRI). The …
proposed for multimodal emotion recognition in human–robot interaction (HRI). The …
A systematic literature review on multimodal machine learning: Applications, challenges, gaps and future directions
Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
CNN and LSTM based facial expression analysis model for a humanoid robot
Robots must be able to recognize human emotions to improve the human-robot interaction
(HRI). This study proposes an emotion recognition system for a humanoid robot. The robot is …
(HRI). This study proposes an emotion recognition system for a humanoid robot. The robot is …
A comprehensive survey on multi-modal conversational emotion recognition with deep learning
Multi-modal conversation emotion recognition (MCER) aims to recognize and track the
speaker's emotional state using text, speech, and visual information in the conversation …
speaker's emotional state using text, speech, and visual information in the conversation …
Semi-supervised multi-modal emotion recognition with cross-modal distribution matching
Automatic emotion recognition is an active research topic with wide range of applications.
Due to the high manual annotation cost and inevitable label ambiguity, the development of …
Due to the high manual annotation cost and inevitable label ambiguity, the development of …
A machine learning-based investigation utilizing the in-text features for the identification of dominant emotion in an email
Identification of emotion hidden in limited text is an active research problem. This work
presents a framework for the same using email text. The present work is based on machine …
presents a framework for the same using email text. The present work is based on machine …