English

FaceChat: An Emotion-Aware Face-to-face Dialogue Framework

Computation and Language 2023-03-14 v1 Artificial Intelligence

Abstract

While current dialogue systems like ChatGPT have made significant advancements in text-based interactions, they often overlook the potential of other modalities in enhancing the overall user experience. We present FaceChat, a web-based dialogue framework that enables emotionally-sensitive and face-to-face conversations. By seamlessly integrating cutting-edge technologies in natural language processing, computer vision, and speech processing, FaceChat delivers a highly immersive and engaging user experience. FaceChat framework has a wide range of potential applications, including counseling, emotional support, and personalized customer service. The system is designed to be simple and flexible as a platform for future researchers to advance the field of multimodal dialogue systems. The code is publicly available at https://github.com/qywu/FaceChat.

Keywords

Cite

@article{arxiv.2303.07316,
  title  = {FaceChat: An Emotion-Aware Face-to-face Dialogue Framework},
  author = {Deema Alnuhait and Qingyang Wu and Zhou Yu},
  journal= {arXiv preprint arXiv:2303.07316},
  year   = {2023}
}
R2 v1 2026-06-28T09:14:42.065Z