Affective Conversational Agents

In this chapter, we revisit the main theories of human emotion and personality and their implications for the development of affective conversational agents. We focus on the role that emotion plays for adapting the agents’ behaviour and how this emotional responsivity can be conveniently modified by rendering a consistent artificial personality. The multiple applications of affective CAs are addressed by describing recent experiences in domains such as pedagogy, computer games, and computer-mediated therapy.

Extending Conversational Agents for Task-Oriented Human-Computer Dialogue

We present the role of conversational agents in two task-oriented human-computer dialogue applications: Interactive Question Answering and Persuasive Dialogue. We show that conversational agents can be effectively deployed for interaction that goes beyond user entertainment and can be successfully used as a means to achieve complex tasks. Conversational agents are a winning solution in Persuasive Dialogue because, combined with a planning infrastructure, they can help manage the parts of the dialogue that cannot be planned a priori and are primordial to keep the system persuasive. In Interactive Question Answering, conversational approaches lead users to the explicit formulation of queries, allow for the submission of further queries and accomodate related queries thanks to their ability to handle context.

Building a Social Conversational Pedagogical Agent

This chapter discusses design challenges encountered when developing a conversational pedagogical agent. By tracing the historical roots of pedagogical agents in Intelligent Tutoring Systems (ITS), we discern central developments in creating an agent that is both knowledgeable and fosters a social relationship with the learner. Main challenges faced when attempting to develop a pedagogical agent of this kind relate to: i) learners’ expectations on the agent’s knowledge and social profile, ii) dealing with learners’ engagement in off-task conversation and iii) managing potential abuse of the agent. We discuss these challenges and possible ways to address them, with reference to an ongoing Research & Development project, and with a focus on the design of a pedagogical agent’s visual embodiment and its conversational capabilities.

Future Trends for Conversational Agents

In the last decades, there has been a great evolution in the field of Conversational Agents. Currently, there are agents to assist the navigation in Web pages, support elder users when interacting with some computer application to remind them which medicines they should take during the day, or to enhance the learning process by allowing students to review with systems that adapt themselves to their previous knowledge and rhythm of study. In this chapter, the goal is to provide a summary of the future trends that can be envisaged for the future of the field. It is our insight that the future of Conversational Agents are to become pervasive and natural in our daily lives.

A Companionable Agent

Companions are agents devised to accompany users day by day building long-term relationships with them. They do not only assist users for particular tasks in sporadic times, but they provide more support and have more information to adapt themselves to each users’ needs. Currently, these agents and their possibilities are being researched as a part of an EU project, which is described in this chapter.

Design and Implementation Issues for Convincing Conversational Agents

This chapter describes a selection of experiences from designing and implementing virtual conversational characters for multimodal dialogue systems. It uses examples from the large interactive narrative VirtualHuman and some related systems of the task-oriented variety. The idea is not to give a comprehensive overview of any one system, but rather to identify and describe some issues that might also be relevant for the designer of a new system, to show how they can be addressed, and what problems still remain unresolved for future work. Besides giving an overview of how characters for interactive narrative systems can be built in the implementation level, the focus is on what should be in the knowledge base for virtual characters, and how it should be organized to be able to provide a convincing interaction with one or multiple characters.

Designing ECAs to Improve Robustness of Human-Machine Dialogue

One of the major challenges for dialogue systems deployed in commercial applications is to improve robustness when common low-level problems occur that are related with speech recognition. We first discuss this important family of interaction problems, and then we discuss the features of non-verbal, visual, communication that Embodied Conversational Agents (ECAs) bring ‘into the picture’ and which may be tapped into to improve spoken dialogue robustness and the general smoothness and efficiency of the interaction between the human and the machine. Our approach is centred around the information provided by ECAs. We deal with all stages of the conversation system development process, from scenario description, to gesture design and evaluation with comparative user tests. We conclude that ECAs can help improve the robustness of, as well as the users’ subjective experience with, a dialogue system. However, they may also make users more demanding and intensify privacy and security concerns.

Embodied Conversational Virtual Patients

Recent research has established the potential for computer generated virtual characters to act as virtual patients (VP) for the assessment and training of novice clinicians in interpersonal skills, interviewing, and diagnosis. These VPs are embodied interactive conversational agents who are designed to simulate a particular clinical presentation of a patient’s illness with a high degree of consistency and realism. In this chapter we describe the architecture developed for virtual patients, and the application of the system to subject testing with virtual patients that exhibit a set of clinical conditions called Post Traumatic Stress Disorder (PTSD). The primary goal of these conversational agents was evaluative: can a VP generate responses that elicit user questions relevant for PTSD categorization? The results of the interactions of clinical students with the VP will be discussed. This chapter also highlights a set of design goals for increasing the visual, physical and cognitive realism when building VP systems including the design of the language, scenarios and artwork that is important when developing these characters. Finally, future research directions and challenges will be discussed for conversational virtual patients.

Enhancement of Conversational Agents By Means of Multimodal Interaction

The main objective of multimodal conversational agents is to provide a more engaged and participative communication by allowing users to employ more than one input methodologies and providing output channels that are different to exclusively using voice. This chapter presents a detailed study on the benefits, disadvantages, and implications of incorporating multimodal interaction in conversational agents. Initially, it focuses on implementation techniques. Next, it explains the fusion and fission of multimodal information and focuses on the core module of these agents: the dialogue manager. Later on, the chapter addresses architectures, tools to develop some typical components of the agents, and evaluation methodologies. As a case of study, it describes the multimodal conversational agent in which we are working at the moment to provide assistance to professors and students in some of their daily activities in an academic centre, for example, a University’s Faculty.

Designing and Evaluating Interactive Agents as Social Skills Tutors for Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) makes communication and social interaction very difficult for those affected. Existing studies have reported positive results for teaching social skills to children with ASD using human-controlled virtual agents and language skills using autonomous agents. Here we combine these approaches and investigate the potential of autonomous agents as social skills tutors. A system for audio-visually synthesising an agent is developed towards this purpose and utilised together with two tutoring modules that we specifically designed for teaching conversation skills and how to deal with bullying. Following evaluation, children’s thoughts about their experience with the virtual tutor were investigated through use of a survey. The positive feedback and the modest but significant improvements in test scores for both modules suggest that this strategy for teaching social skills has much potential and that further research and development in this area would be eminently worthwhile.