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<Paper uid="H01-1062">
  <Title>The RWTH System for Statistical Translation of Spoken Dialogues</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1. INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> In comparison with written language, speech and especially spontaneous speech poses additional difficulties for the task of automatic translation. Typically, these difficulties are caused by errors of the recognition process, which is carried out before the translation process. As a result, the sentence to be translated is not necessarily well-formed from a syntactic point-of-view. Even without recognition errors, speech translation has to cope with a lack of conventional syntactic structures because the structures of spontaneous speech differ from that of written language.</Paragraph>
    <Paragraph position="1"> The statistical approach shows the potential to tackle these problems for the following reasons. First, the statistical approach is able to avoid hard decisions at any level of the translation process. Second, for any source sentence, a translated sentence in the target language is guaranteed to be generated. In most cases, this will be hopefully a syntactically perfect sentence in the target language; but even if this is not the case, in most cases, the translated sentence will convey the meaning of the spoken sentence.</Paragraph>
    <Paragraph position="2"> .</Paragraph>
    <Paragraph position="3"> Whereas statistical modelling is widely used in speech recognition, there are so far only a few research groups that apply statistical modelling to language translation. The presentation here is based on work carried out in the framework of the EuTrans project [8] and the Verbmobil project [25].</Paragraph>
  </Section>
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