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We present LISSA — Live Interactive Social Skill Assistance — a web-based system that helps people practice their conversational skills by having short conversations with a human like virtual agent and receiving real-time feedback on their nonverbal behavior. In this paper, we describe the development of an interface for these features and examine the viability of real time feedback using a Wizard...
Ever wondered why you have been rejected from a job despite being a qualified candidate? What went wrong? In this paper, we provide a computational framework to quantify human behavior in the context of job interviews. We build a model by analyzing 138 recorded interview videos (total duration of 10.5 hours) of 69 internship-seeking students from Massachusetts Institute of Technology (MIT) as they...
Effective video-conferencing conversations are heavily influenced by each speaker's facial expression. In this study, we propose a novel probabilistic model to represent interactional synchrony of conversation partners' facial expressions in video-conferencing communication. In particular, we use a hidden Markov model (HMM) to capture temporal properties of each speaker's facial expression sequence...
Automated nonverbal sensing and feedback technologies, such as My Automated Conversation coacH (MACH), can provide a personalized means to better understand, evaluate, and improve human social interaction--for both practical and therapeutic purposes, and to advance future communications research. The first Web extra at http://youtu.be/l3ztu9shfMg discusses My Automated Conversation coacH (MACH), a...
We create two experimental situations to elicit two affective states: frustration, and delight. In the first experiment, participants were asked to recall situations while expressing either delight or frustration, while the second experiment tried to elicit these states naturally through a frustrating experience and through a delightful video. There were two significant differences in the nature of...
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