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<Paper uid="P06-2051">
  <Title>Spontaneous Speech Understanding for Robust Multi-Modal Human-Robot Communication</Title>
  <Section position="10" start_page="396" end_page="397" type="concl">
    <SectionTitle>
8 Conclusion and Outlook
</SectionTitle>
    <Paragraph position="0"> In this paper we have presented a new approach of robust speech understanding for mobile robot assistants. It takes into account the special characteristics of situated communication and also the dif culty for the speech recognition to process utterances correctly. We use special concept structures for situated communication combined with an automatic fusion mechanism to generate semantic structures which are necessary for the dialog manager of the robot system in order to respond adequately.</Paragraph>
    <Paragraph position="1"> This mechanism combined with the use of our  SSUs has several bene ts. First, speech is interpreted even if speech recognition does not always guarantee correct results and speech input is not always grammatically correct. Secondly, the speech understanding component incorporates information about gestures and references to the environment. Furthermore, the mechanism itself is domain-independent. Both, concepts and lexicon can be exchanged in context of a different domain. This semantic analysis already produces elaborated interpretations of utterances in a fast way and furthermore, helps to improve robustness of the entire speech processing system. Nevertheless, we can improve the system. In our next phase we will use a more elaborate scoring function technique and use the correlations of mandatory and optional links to other concepts to perform a better evaluation and also to help the dialog manager to nd clues for missing information both in speech and scene. We will also use the evaluation results to improve the SSUs to get better results for the semantic interpretation.</Paragraph>
  </Section>
class="xml-element"></Paper>