Life-like Agents Research Articles

A Comparative Japanese-U.S. Study of the Acceptability of Conversational Lifelike Agents for Linguistic Consideration

A Comparative Japanese-U.S. Study of the Acceptability of Conversational Lifelike Agents for Linguistic Consideration

Appropriateness of Ambiguous Facial Expressions Shown by Life-like Agents in Relation to Context of Communication

Appropriateness of Ambiguous Facial Expressions Shown by Life-like Agents in Relation to Context of Communication

A Text-Based Chat System Embodied with an Expressive Agent

Life-like characters are playing vital role in social computing by making human-computer interaction more easy and spontaneous. Nowadays, use of these characters to interact in online virtual environment has gained immense popularity. In this paper, we proposed a framework for a text-based chat system embodied with a life-like virtual agent that aims at natural communication between the users. To achieve this kind of system, we developed an agent that performs some nonverbal communications such as generating facial expression and motions by analyzing the text messages of the users. More specifically, this agent is capable of generating facial expressions for six basic emotions such as happy, sad, fear, angry, surprise, and disgust along with two additional emotions, irony and determined. Then to make the interaction between the users more realistic and lively, we added motions such as eye blink and head movements. We measured our proposed system from different aspects and found the results satisfactory, which make us believe that this kind of system can play a significant role in making an interaction episode more natural, effective, and interesting. Experimental evaluation reveals that the proposed agent can display emotive expressions correctly 93% of the time by analyzing the users’ text input.

Affective Tutoring System for Better Learning

Intelligent tutoring systems (ITS) are still not as effective as one-on-one human tutoring. The next generation of intelligent tutors are expected to be able to take into account the emotional state of students. This paper presents research on the development of an Affective Tutoring System (ATS). The system called “Easy with Eve” adapts to students via a lifelike animated agent who is able to detect student emotion through facial expression analysis, and can display emotion herself. Eve’s adaptations are guided by a case-based method for adapting to student states; this method uses data that was generated by an observational study of human tutors. This paper presents an analysis of facial expressions of students engaged in learning with human tutors and how a facial expression recognition system, a life like agent and a case based system based on this analysis have been integrated to develop an ATS for mathematics.

AUTOMATIC GENERATION OF GAZE AND GESTURES FOR DIALOGUES BETWEEN EMBODIED CONVERSATIONAL AGENTS

In this paper we introduce a system that automatically adds different types of non-verbal behavior to a given dialogue script between two virtual embodied agents. It allows us to transform a dialogue in text format into an agent behavior script enriched by eye gaze and conversational gesture behavior. The agents' gaze behavior is informed by theories of human face-to-face gaze behavior. Gestures are generated based on the analysis of linguistic and contextual information of the input text. The resulting annotated dialogue script is then transformed into the Multimodal Presentation Markup Language for 3D agents (MPML3D), which controls the multi-modal behavior of animated life-like agents, including facial and body animation and synthetic speech. Using our system makes it very easy to add appropriate non-verbal behavior to a given dialogue text, a task that would otherwise be very cumbersome and time consuming. In order to test the quality of gaze generation, we conducted an empirical study. The results showed that by using our system, the naturalness of the agents' behavior was not increased when compared to randomly selected gaze behavior, but the quality of the communication between the two agents was perceived as significantly enhanced.

Variety of Robot Behaviors for Human-Robot Interactions Using Attention

Abstract Human-robot interaction (HRI) is essential in order for robots to play a role in everyday life. To achieve this, one problem is the fixation of robot’s reaction. In many existing HRI systems, the behavior of robots is fixed to each situation which is assumed beforehand. The human can easily predict the robot’s reaction in such case and becomes to feel the robot as not an life-like agent but a toy. To solve this problem, we propose a novel model of attention, named Feature Drift. With Feature Drift, a robot can determine its attention spontaneously and change its attention over time. By changing robot’s attention, the robot becomes to react variously, not fixed. This study evaluates the behavior of Feature Drift model in simulation and designs an HRI system. We also test the HRI system, and then confirms that the system can generate various reactions.

“How do you know that I don’t understand?” A look at the future of intelligent tutoring systems

Many software systems would significantly improve performance if they could adapt to the emotional state of the user, for example if Intelligent Tutoring Systems (ITSs), ATM’s, ticketing machines could recognise when users were confused, frustrated or angry they could guide the user back to remedial help systems so improving the service. Many researchers now feel strongly that ITSs would be significantly enhanced if computers could adapt to the emotions of students. This idea has spawned the developing field of affective tutoring systems (ATSs): ATSs are ITSs that are able to adapt to the affective state of students. The term “affective tutoring system” can be traced back as far as Rosalind Picard’s book Affective Computing in 1997. This paper presents research leading to the development of Easy with Eve, an ATS for primary school mathematics. The system utilises a network of computer systems, mainly embedded devices to detect student emotion and other significant bio-signals. It will then adapt to students and displays emotion via a lifelike agent called Eve. Eve’s tutoring adaptations are guided by a case-based method for adapting to student states; this method uses data that was generated by an observational study of human tutors. This paper presents the observational study, the case-based method, the ATS itself and its implementation on a distributed computer systems for real-time performance, and finally the implications of the findings for Human Computer Interaction in general and e-learning in particular. Web-based applications of the technology developed in this research are discussed throughout the paper.

Realising emergent image preprocessing tasks in cellular-automaton-alike massively parallel hardware

In this paper, we present an emergent computing architecture scheme, denoted as marching pixels (MPs), which is well-suited for massively-parallel embedded systems based realising smart optical sensors. Smart in this context refers to sensors in which signal capturing and signal processing is combined either in one chip or in a compact 3D chip stack. MPs are life-like agents, which are crawling within a pixel field in such a chip in order to find centre points and other attributes of objects in binary images. MPs fulfill these tasks only by utilising local interaction and stigmertic communication. Principal ideas, the architecture and first results are described in this paper along with a comparison to both conventional and other unconventional computing approaches.

Symmetric Multimodality Revisited: Unveiling Users' Physiological Activity

In this paper, we describe our own stance on a research area called Humatronics, which aims at establishing a (more) symmetric interaction relationship between and computer systems. In particular, we will advocate a novel approach to understanding that is based on largely involuntary and unconscious physiological information and gaze behavior rather than purposeful and conscious actions or behaviors. Understanding humans here refers to users' states related to emotion and affect, attention and interest, and possibly even to their intentions. A key feature of our approach is that it provides insight into a person's cognitive-motivational state without relying on cognitive judgements, such as answers to dedicated queries. Lifelike interface agents are endowed with synthetic bodies and faces and can be considered as prime candidates for outbalancing the asymmetric relationship in current human-computer interaction. As example applications, we will report on two recent studies that utilized lifelike agents as presenters or interaction partners of users. The resulting interactions can be conceived as implementing initial steps toward symmetric multimodality in user interfaces

Describing and generating multimodal contents featuring affective lifelike agents with MPML

In this paper, we provide an overview of our research on multimodal media and contents using embodied lifelike agents. In particular we describe our research centered on MPML (Multimodal Presentati...

Interaction Builder: A Rapid Prototyping Tool for Developing Web-Based MMI Applications

We have developed Interaction Builder (IB), a rapid prototyping tool for constructing web-based Multi-Modal Interaction (MMI) applications. The goal of IB is making it easy to develop MMI applications with speech recognition, life-like agents, speech synthesis, web browsing, etc. For this purpose, IB supports the following interface and functions: (1) GUI for implementing MMI systems without the details of MMI and MMI description language, (2) functionalities of handling synchronized multimodal inputs/outputs, (3) a test run mode for run-time testing. The results of evaluation tests showed that the application development cycle using IB was significantly shortened in comparison with the time using a text editor both for MMI description language experts and for beginners.

Special Section on Life-like Agent and its Communication

Special Section on Life-like Agent and its Communication

エージェント媒介型表情コミュニケーションにおける利用者の主観に基づく表情マッピングの獲得(<論文特集>IDEA: 適応のためのインタラクション設計)

遠隔コミュニケーションにおいて, 利用者の表情を擬人化エージェントによって伝達するエージェント媒介型表情コミュニケーションでは, 利用者と擬人化エージェントという異なる顔による表情の間で, お互いに同一のもの同士を対応付ける表情マッピングが必要となる.この表情マッピングとして具体的にどのような対応付けが望ましいかは個人の主観に依存することから, 本研究ではこれをエージェント媒介型表情コミュニケーションのための利用者とのインタラクションを利用して獲得することを目指す.このとき, 獲得した表情マッピングが利用者の満足するものとなるには, 表情マッピングの対応付けが, 利用者の主観に一致したものとなっていることに加えて, それを実現する際の誤差が, 利用者の許容範囲内に収まっている必要がある.本研究ではこれら2点を考慮し, 表情マッピングに対して利用者の要求する対応付けと利用者の許容する誤差範囲を, 利用者とのインタラクションによって得られる事例から推定すると共に, それらを実現する表情マッピングをRBF (Radial Basis Function)ネットワークを用いて学習する手法を提案する.

人間と擬人化エージェントによるマインドマッピングの相互適応(<論文特集>IDEA: 適応のためのインタラクション設計)

人間と擬人化エージェントによるマインドマッピングの相互適応(<論文特集>IDEA: 適応のためのインタラクション設計)

Mutual Adaptation between a Human and a Life-like agent in a mind-reading game

Mutual Adaptation between a Human and a Life-like agent in a mind-reading game

Mutual Adaptaion in Communication between a Human and a Life-like Agent by Sharing Contextdependent Facial Expressions

Mutual Adaptaion in Communication between a Human and a Life-like Agent by Sharing Contextdependent Facial Expressions

Behavioral Self-Organization in Lifelike Synthetic Agents

Modern computer graphics technology has enjoyed rapid development in recent years, attracting researchers and practitioners to explore a wide spectrum of applications ranging from computer-aided graphical design to artificial life and virtual reality. This paper is concerned with the animation-based entertainment use of computer graphics, i.e., to create digitally synthetic agents that can self-animate themselves, adapt to their virtual environments, and learn new behaviors to attain some specific goals. Here we propose a synthetic agent computational architecture called inter-threaded motif-based behavioral self-organization architecture, in which one motif acquires a conditioned association from the presently sensed state of the environment to the requirement of a desired motion as well as a plausible behavioral pattern to enable such a motion, whereas another computes the optimal parameters for the identified behavior in fulfilling the motion requirement. This architecture will enable animated behaviors to be automatically programmed based on the concurrent self-organization of individual motifs as well as their crisscrossing interactions.

Enhancing Conversational Flexibility in Multimodal Interactions with Embodied Lifelike Agents

Enhancing Conversational Flexibility in Multimodal Interactions with Embodied Lifelike Agents

Deictic believability: Coordinated gesture, locomotion, and speech in lifelike pedagogical agents

Lifelike animated agents for knowledge - based learning environments can provide timely , customized advice to support students' problem solving . Because of their strong visual presence , they hold significant promise for substantially increasing students' enjoyment of their learning experiences . A key problemposed by lifelike agents that inhabit artificial worlds is deictic believability. In the same manner that humans refer to objects in their environment through judicious combinations of speech , locomotion , and gesture , animated agents should be able to move through their environment and point to and refer to objects appropriately as they provide problem - solving advice . In this paper we describe a framework for achieving deictic believability in animated agents . A deictic behavior planner exploits a world model and the evolving explanation plan as it selects and coordinates locomotive , gestural , and speech behaviors . The resulting behaviors and utterances are believable , and the references exhibit a lack of ambiguity . This approach to spatial deixis has been implemented in a lifelike animated agent , COSMO , who inhabits a learning environment for the domain of Internet packet routing . COSMO provides real - time advice to students as they escort packets through a virtual world of interconnected routers . Results of an informal focus group study with the COSMOagent suggest that the spatial deixis framework produces clear explanatory animated behaviors .

Conferring human action recognition skills to life-like agents

Most of today's virtual environments are populated with some kind of autonomous life - like agents . Such agents follow a preprogrammed sequence of behaviors that excludes the user as a participating entity in the virtual society . In order to make inhabited virtual reality an attractive place for information exchange and social interaction , we need to equip the autonomous agents with some perception and interpretation skills . In this paper we present one skill: human action recognition . By opposition to human - computer interfaces that focus on speech or hand gestures , we propose a full - body integration of the user . We present a model of human actions along with a real - time recognition system . To cover the bilateral aspect in human - computer interfaces , we also discuss some action response issues . In particular , we describe a motion management library that solves animation continuity and mixing problems . Finally , we illustrate our systemwith two examples and discuss what we have learned .