2 citations · 7 across the 14 of their papers we have counts for
6 papers · 1 filter
Learning More with Less: Self-Supervised Approaches for Low-Resource Speech Emotion Recognition
Ziwei Gong, Pengyuan Shi, Kaan Donbekci +5
Speech Emotion Recognition (SER) has seen significant progress with deep learning, yet remains challenging for Low-Resource Languages (LRLs) due to the scarcity of annotated data.…
Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects
Chengyan Wu, Yiqiang Cai, Yang Liu +5
While text-based emotion recognition methods have achieved notable success, real-world dialogue systems often demand a more nuanced emotional understanding than any single modality…
A Review of Incorporating Psychological Theories in LLMs
Zizhou Liu, Ziwei Gong, Lin Ai +5
Psychological insights have long shaped pivotal NLP breakthroughs, from attention mechanisms to reinforcement learning and social modeling. As Large Language Models (LLMs) develop,…
Personalized Attacks of Social Engineering in Multi-turn Conversations: LLM Agents for Simulation and Detection
Tharindu Kumarage, Cameron Johnson, Jadie Adams +7
The rapid advancement of conversational agents, particularly chatbots powered by Large Language Models (LLMs), poses a significant risk of social engineering (SE) attacks on social…
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges
Bolei Ma, Yuting Li, Wei Zhou +7
Understanding pragmatics-the use of language in context-is crucial for developing NLP systems capable of interpreting nuanced language use. Despite recent advances in language tech…
Akan Cinematic Emotions (ACE): A Multimodal Multi-party Dataset for Emotion Recognition in Movie Dialogues
David Sasu, Zehui Wu, Ziwei Gong +5
In this paper, we introduce the Akan Conversation Emotion (ACE) dataset, the first multimodal emotion dialogue dataset for an African language, addressing the significant lack of r…