Our paper investigates the utility of speech signals for AI-based depression detection, including different interaction scenarios, speech processing techniques, and feature types.
It is so great to return to academia, especially come to such an international university. We warmly welcome all types of collaboration from both the academic and industrial sectors.
Our paper proposes a novel approach, which integrates three components - emotion cause, knowledge graph, and communication mechanism for empathetic response generation in a dialogue system.
Our paper proposes a collaborative learning framework for unsupervised text style transfer using a pair of bidirectional decoders and achieves strong empirical results on both style compatibility and content preservation.
Our paper proposes a meta learning approach to solve the problem of user-defined spoken term classification with varying classes and examples.
I am lucky to join the CUHK AIoT Lab as postdoctoral research fellow, working with Prof. Guoliang Xing and many intelligent PostDocs and PhD studends.
I am grduated from the Department of Computer Science in City University of Hong Kong. Thanks to my family, friends, supervisors, collaborators, and all those people who give me love and power. (Those who are interested in my PhD research can view my thesis and slides.)