4 accepted papers
Text-driven human motion generation has attracted considerable critical attention in recent years. The task requires generating movements that are diverse, natural, and comfortable in accordance with the text description. However, while generating the human motion, there is a significant gap in the…
Multimodal Emotion Recognition in Conversations (ERC) plays a crucial role in understanding human language and behavior in real-world scenarios. However, existing research tends to simply concatenate multimodal representations, failing to capture the complex relationships between modalities. Recent…
The Pre-trained Speech Models (PSMs) generate universal speech representations using self-supervised or weakly-supervised learning from large-scale datasets. It achieves promising performance when fine-tuned for specific tasks such as Speech Emotion Recognition (SER). However, fine-tuning on various…
Federal learning-based (FL) Speech Emotion Recognition (SER) framework aims to protect data privacy when characterizing emotions. However, previous studies have shown that the framework is vulnerable, because curious servers can indirectly infer user private information. To address this challenge, w…