In this paper, we present our work in building technologies for natural multimodal human-robot interaction. We present our systems for spontaneous speech recognition, multimodal dialogue processing, and visual perception of a user, which includes localization, tracking, and identification of the user, recognition of pointing gestures, as well as the recognition of a person's head orientation. Each of the components is described in the paper and experimental results are presented. We also present several experiments on multimodal human-robot interaction, such as interaction using speech and gestures, the automatic determination of the addressee during human-human-robot interaction, as well on interactive learning of dialogue strategies. The work and the components presented here constitute the core building blocks for audiovisual perception of humans and multimodal human-robot interaction used for the humanoid robot developed within the German research project (Sonderforschungsbereich) on humanoid cooperative robots.
Abstract. This paper describes the Ephyra question answering engine, a modular and extensible framework that allows to integrate multiple approaches to question answering in one system. Our framework can be adapted to languages other than English by replacing language-specific components. It supports the two major approaches to question answering, knowledge annotation and knowledge mining. Ephyra uses the web as a data resource, but could also work with smaller corpora. In addition, we propose a novel approach to question interpretation which abstracts from the original formulation of the question. Text patterns are used to interpret a question and to extract answers from text snippets. Our system automatically learns the patterns for answer extraction, using question-answer pairs as training data. Experimental results revealed the potential of this approach.
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