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Transformer models for text-based emotion detection: a review of BERT-based approaches
We cannot overemphasize the essence of contextual information in most natural language
processing (NLP) applications. The extraction of context yields significant improvements in …
processing (NLP) applications. The extraction of context yields significant improvements in …
Emotion recognition in conversation: Research challenges, datasets, and recent advances
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 …
human-like artificial intelligence (AI). Emotion recognition in conversation (ERC) is …
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 develo** sympathetic
human-machine interaction. In conversational videos, emotion can be present in multiple …
human-machine interaction. In conversational videos, emotion can be present in multiple …
MMGCN: Multimodal fusion via deep graph convolution network for emotion recognition in conversation
The CANDOR corpus: Insights from a large multimodal dataset of naturalistic conversation
People spend a substantial portion of their lives engaged in conversation, and yet, our
scientific understanding of conversation is still in its infancy. Here, we introduce a large …
scientific understanding of conversation is still in its infancy. Here, we introduce a large …
Emotionqueen: A benchmark for evaluating empathy of large language models
Emotional intelligence in large language models (LLMs) is of great importance in Natural
Language Processing. However, the previous research mainly focus on basic sentiment …
Language Processing. However, the previous research mainly focus on basic sentiment …