Emotion recognition in conversation: Research challenges, datasets, and recent advances

S Poria, N Majumder, R Mihalcea, E Hovy - IEEE access, 2019 - ieeexplore.ieee.org
Emotion is intrinsic to humans and consequently, emotion understanding is a key part of
human-like artificial intelligence (AI). Emotion recognition in conversation (ERC) is …

A survey on empathetic dialogue systems

Y Ma, KL Nguyen, FZ Xing, E Cambria - Information Fusion, 2020 - Elsevier
Dialogue systems have achieved growing success in many areas thanks to the rapid
advances of machine learning techniques. In the quest for generating more human-like …

Cosmic: Commonsense knowledge for emotion identification in conversations

D Ghosal, N Majumder, A Gelbukh, R Mihalcea… - arXiv preprint arXiv …, 2020 - arxiv.org
In this paper, we address the task of utterance level emotion recognition in conversations
using commonsense knowledge. We propose COSMIC, a new framework that incorporates …

M2fnet: Multi-modal fusion network for emotion recognition in conversation

V Chudasama, P Kar, A Gudmalwar… - Proceedings of the …, 2022 - openaccess.thecvf.com
Abstract Emotion Recognition in Conversations (ERC) is crucial in developing sympathetic
human-machine interaction. In conversational videos, emotion can be present in multiple …

Directed acyclic graph network for conversational emotion recognition

W Shen, S Wu, Y Yang, X Quan - arXiv preprint arXiv:2105.12907, 2021 - arxiv.org
The modeling of conversational context plays a vital role in emotion recognition from
conversation (ERC). In this paper, we put forward a novel idea of encoding the utterances …

Dialoguegcn: A graph convolutional neural network for emotion recognition in conversation

D Ghosal, N Majumder, S Poria, N Chhaya… - arXiv preprint arXiv …, 2019 - arxiv.org
Emotion recognition in conversation (ERC) has received much attention, lately, from
researchers due to its potential widespread applications in diverse areas, such as health …

Integrating multimodal information in large pretrained transformers

W Rahman, MK Hasan, S Lee, A Zadeh, C Mao… - arXiv preprint arXiv …, 2019 - arxiv.org
Recent Transformer-based contextual word representations, including BERT and XLNet,
have shown state-of-the-art performance in multiple disciplines within NLP. Fine-tuning the …

Dialoguernn: An attentive rnn for emotion detection in conversations

N Majumder, S Poria, D Hazarika, R Mihalcea… - Proceedings of the …, 2019 - ojs.aaai.org
Emotion detection in conversations is a necessary step for a number of applications,
including opinion mining over chat history, social media threads, debates, argumentation …

Sentiment analysis: A survey on design framework, applications and future scopes

M Bordoloi, SK Biswas - Artificial intelligence review, 2023 - Springer
Sentiment analysis is a solution that enables the extraction of a summarized opinion or
minute sentimental details regarding any topic or context from a voluminous source of data …

Dialoguecrn: Contextual reasoning networks for emotion recognition in conversations

D Hu, L Wei, X Huai - arXiv preprint arXiv:2106.01978, 2021 - arxiv.org
Emotion Recognition in Conversations (ERC) has gained increasing attention for
developing empathetic machines. Recently, many approaches have been devoted to …