We present a demonstration of the ARIA framework, a modular approach for rapid development of virtual humans for information retrieval that have linguistic, emotional, and social skills and a strong personality. We demonstrate the framework's capabilities in a scenario where 'Alice in Wonderland', a popular English literature book, is embodied by a virtual human representing Alice. The user can engage in an information exchange dialogue, where Alice acts as the expert on the book, and the user as an interested novice. Besides speech recognition, sophisticated audio-visual behaviour analysis is used to inform the core agent dialogue module about the user's state and intentions, so that it can go beyond simple chat-bot dialogue. The behaviour generation module features a unique new capability of being able to deal gracefully with interruptions of the agent.
We present a new dialogue engine called Flipper 2.0 (Flipper) which aims to help developers of embodied conversational agents (ECAs) to quickly and flexibly create dialogues. Flipper provides a technically stable and robust dialogue management system to integrate with other components of ECAs such as behaviour realisers. We compare Flipper with state-of-the-art dialogue design systems. We describe the details of our dialogue engine, how it handles dialogue management and how it supports the authoring of dialogues. We demonstrate the use of the dialogue engine with examples of design patterns and discuss practical applications. Finally we give recommendations on the cases in which it is beneficial to use Flipper. CCS CONCEPTS• Human-centered computing → Natural language interfaces; Systems and tools for interaction design; User interface toolkits;• Information systems → Open source software; KEYWORDS dialogue manager, dialogue engine, dialogue design, pragmatics, embodied conversational agent ACM Reference Format:
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In this study, we have developed a voicebot which asks users questions about their daily activities and social participation to gain insights into their happiness and well-being. We hypothesize that showing disclosure when asking questions can elicit reciprocity of self-disclosure by the users. We define two types of disclosure: selfdisclosure and other-disclosure. Self-disclosure is sharing thoughts, feelings and information about oneself, whereas other-disclosure is sharing information about others and opinions of others. We analyzed 122 answers to the voicebot's disclosure and control questions by annotating the number of self-disclosure statements in the answers. We found no significant effect of asking disclosure questions on the number of self-disclosure statements. However, we did find a positive effect of asking disclosure questions on common markers of reciprocity such as the number of words, topic phrases, and first-person pronouns. Replication of this study with more participants would strengthen the validity of the findings. CCS CONCEPTS• Human-centered computing → Empirical studies in interaction design; Sound-based input / output; Web-based interaction.
This work was part of the research programme Data2Person with project number 628.011.029, which is (partly) financed by the Dutch Research Council (NWO). SIKS Dissertation Series No. 2021-27. The research reported in this thesis has been carried out under the auspices of SIKS,
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