Abstract. We present an intelligent embodied conversation agent with linguistic, social and emotional competence. Unlike the vast majority of the state-of-the-art conversation agents, the proposed agent is constructed around an ontology-based knowledge model that allows for flexible reasoning-driven dialogue planning, instead of using predefined dialogue scripts. It is further complemented by multimodal communication analysis and generation modules and a search engine for the retrieval of multimedia background content from the web needed for conducting a conversation on a given topic. The evaluation of the 1st prototype of the agent shows a high degree of acceptance of the agent by the users with respect to its trustworthiness, naturalness, etc. The individual technologies are being further improved in the 2nd prototype.
In this work, we investigate whether the cultural idiosyncrasies found in humanhuman interaction may be transferred to human-computer interaction. With the aim of designing a culture-sensitive dialogue system, we designed a user study creating a dialogue in a domain that has the potential capacity to reveal cultural differences. The dialogue contains different options for the system output according to cultural differences. We conducted a survey among Germans and Japanese to investigate whether the supposed differences may be applied in human-computer interaction. Our results show that there are indeed differences, but not all results are consistent with the cultural models.
In this paper, we investigate the applicability of soft changes to the system behaviour, namely changing the amount of elaborateness and indirectness displayed. To this end, we examine the impact of elaborateness and indirectness on the perception of human-computer communication in a user study. Here, we show that elaborateness and indirectness influence the user's impression of a dialogue and discuss the implications of our results for adaptive dialogue management. We conclude that elaborateness and indirectness offer valuable possibilities for adaptation and should be incorporated in adaptive dialogue management.
In this paper, we describe the principles and technologies that underpin the development of an adaptive dialogue manager framework, tailored to carrying out human-agent conversations in a natural, robust and flexible manner. Our research focus is twofold. First, the investigation of dialogue strategies that can handle dynamically created user and system actions, while still enabling the agent to adapt its actions to various and possibly changing contexts. Second, the utilisation of rich semantic annotations for capturing background knowledge, as well as conversation topics and semantics of user utterances extracted through language analysis. The resulting annotations comprise the situational descriptions upon which reasoning takes place to recognise the conversation context and compile appropriate responses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.