44,195 research outputs found
I Probe, Therefore I Am: Designing a Virtual Journalist with Human Emotions
By utilizing different communication channels, such as verbal language,
gestures or facial expressions, virtually embodied interactive humans hold a
unique potential to bridge the gap between human-computer interaction and
actual interhuman communication. The use of virtual humans is consequently
becoming increasingly popular in a wide range of areas where such a natural
communication might be beneficial, including entertainment, education, mental
health research and beyond. Behind this development lies a series of
technological advances in a multitude of disciplines, most notably natural
language processing, computer vision, and speech synthesis. In this paper we
discuss a Virtual Human Journalist, a project employing a number of novel
solutions from these disciplines with the goal to demonstrate their viability
by producing a humanoid conversational agent capable of naturally eliciting and
reacting to information from a human user. A set of qualitative and
quantitative evaluation sessions demonstrated the technical feasibility of the
system whilst uncovering a number of deficits in its capacity to engage users
in a way that would be perceived as natural and emotionally engaging. We argue
that naturalness should not always be seen as a desirable goal and suggest that
deliberately suppressing the naturalness of virtual human interactions, such as
by altering its personality cues, might in some cases yield more desirable
results.Comment: eNTERFACE16 proceeding
The state-of-the-art in personalized recommender systems for social networking
With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0
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