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

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arxiv 2303.07316 v1 pith:CPGKOZBM submitted 2023-03-08 cs.CL cs.AI

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

classification cs.CL cs.AI
keywords facechatdialogueframeworkexperienceface-to-facepotentialprocessingsystems
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 1 Pith paper

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    A holistic survey of affective computing for intelligent agents covering emotion understanding via multimodal data, affective cognition, emotional expression synthesis, key challenges, and future directions emphasizin...