Intelligent Virtual Humans with Autonomy and Personality: State-of-the-Art

Kasap, Zerrin; Magnenat‐Thalmann, Nadia

doi:10.1007/978-3-540-79868-2_2

Cited by 29 publications

(22 citation statements)

References 95 publications

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“…According to similar interpretation of the environment, people decide what to do with the current situation and select among different alternative actions that move to a better state [2]. Our framework is based on plan based approach which is more complex than any other approaches and originates from the idea that humans communicate to achieve a particular goal [2].…”

Section: Figure 1: Human Computer Interaction Interface Designmentioning

confidence: 99%

“…Our framework is based on plan based approach which is more complex than any other approaches and originates from the idea that humans communicate to achieve a particular goal [2]. Dialogue manager is basically responsible for initializing values, updating the information state and presenting it to the Action & Query Manager (AQM) module.…”

Section: Figure 1: Human Computer Interaction Interface Designmentioning

confidence: 99%

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A Model to Incorporate Emotional Sensitivity into Human Computer Interactions

Ramnani

Gorthi

2014

Proceedings of the 2014 Workshop on Emotion Representation and Modelling in Human-Computer-Interaction-Systems

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Human machine interaction has started receiving much attention in recent years. The 'Link' which plays a major role in interfacing and facilitating human machine interaction, is getting more and more equipped with different modalities (such as natural language processing , intelligent reasoning etc.) so as to shift the cognitive load of understanding from human to machine. This makes machines not only be able to respond in more appropriate and relevant ways but also reduces the human efforts (in making the system understand and act) to the extent possible. This research work contributes to the design and implementation of the interface by presenting a unified model that takes human machine interaction to a advanced level of understanding with an intelligent interface that not only consists of incorporating emotional intelligence into machines but also identifying contextual information, intention recognition (for a given user's textual response) leading to strategic adaptive dialogue management. The motivation for the system proposed is to provide an inexpensive, unobtrusive means for human beings to interact with computer applications in a meaningful way that requires minimal effort. Research work is completely dedicated to provide a baseline mechanism for achieving stress free satisfying interaction between human and machines. Our system is tested against the existing IVR technology and corresponding results are captured.

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Section: Figure 1: Human Computer Interaction Interface Designmentioning

confidence: 99%

Section: Figure 1: Human Computer Interaction Interface Designmentioning

confidence: 99%

A Model to Incorporate Emotional Sensitivity into Human Computer Interactions

Ramnani

Gorthi

2014

Proceedings of the 2014 Workshop on Emotion Representation and Modelling in Human-Computer-Interaction-Systems

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“…During the last decade, virtual humans became very popular in gaming, entertainment, and social media [17]. Research has demonstrated that enhancing virtual reality with digital characters will fundamentally allow us to interact with computers in a human way and on a personalized basis [31].…”

Section: From Voice-only To Immersive Vpamentioning

confidence: 99%

A model to measure QoE for virtual personal assistant

Saad

Afzal

El-Issawi

et al. 2016

Multimed Tools Appl

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Until now the virtual assistants (like Siri, Google Now and Cortana) have primarily been confined to voice input and output only. Is there a justification for voice only confinement or can we enhance the user experience by adding a visual output? We hypothesized that providing a higher level of visual/auditory immersion would enhance the quality of user experience. In order to test this hypothesis, we first developed 4 variants of virtual assistant, each with a different audio/visual level of immersion. Developed virtual assistant systems were the following; audio only, audio and 2D visual display, audio and 3D visual display and audio and immersive 3D visual display. We developed a plan for usability testing of all 4 variants. The usability testing was conducted with 30 subjects against eight (8) dependent variables included presence, involvement, attention, reliability, dependency, easiness, satisfaction and expectations. Each subject rated these dependent variables based on a scale of 1-5, 5 being the highest value. The raw data collected from usability testing was then analyzed through several tools in order to determine the factors contributing towards the quality of experience for each of the 4 variants. The significant factors were then used develop a model that measures the quality of user experience. It was found that each variant had a different set of significant variables. Hence, in order to rate each system there is a need to develop a scale that is dependent upon the unique set of variables for the respective variant. Furthermore, it was found that variant 4 scored the highest rate for Quality of Experience (QoE). Lastly several other qualitative conclusions were also drawn from this research that will guide future work in the field of virtual assistants.

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“…Therefore, the respective environmental knowledge, as well as the generated actions is usually encoded in conceptual, symbolic forms, capable of expressing high-level, abstract semantics and compatible with the cognition processes supporting them. On the contrary, virtual environments are typically modelled according to low-level, platform-dependent symbols, which are quite efficient in both expressing detailed geometrical and appearance-related data, as well as effectively hiding deducible higher-level semantics [1], [6]. These approaches in modelling an IVA have been successful on tasks requiring high-level cognition, but they have been quite unsuccessful on everyday tasks that humans find extremely easy to manage.…”

Section: Designing Autonomous Artificial Agentsmentioning

confidence: 99%

Autonomy in Virtual Agents: Integrating Perception and Action on Functionally Grounded Representations

Arnellos

Vosinakis

Anastasakis

et al.

Artificial Intelligence: Theories, Models and Applications

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Abstract. Autonomy is a fundamental property for an intelligent virtual agent. The problem in the design of an autonomous IVA is that the respective models approach the interactive, environmental and representational aspects of the agent as separate to each other, while the situation in biological agents is quite different. A theoretical framework indicating the fundamental properties and characteristics of an autonomous biological agent is briefly presented and the interactivist model of representations combined with the concept of a semiotic process are used as a way to provide a detailed architecture of an autonomous agent and its fundamental characteristics. A part of the architecture is implemented as a case study and the results are critically discussed showing that such architecture may provide grounded representational structures, while issues of scaling are more difficult to be tackled.

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Intelligent Virtual Humans with Autonomy and Personality: State-of-the-Art

Cited by 29 publications

References 95 publications

A Model to Incorporate Emotional Sensitivity into Human Computer Interactions

A Model to Incorporate Emotional Sensitivity into Human Computer Interactions

A model to measure QoE for virtual personal assistant

Autonomy in Virtual Agents: Integrating Perception and Action on Functionally Grounded Representations

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