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<Paper uid="C00-2098">
  <Title>A Context-Sensitive Model for Probabilistie LR Parsing of Spoken Language with Transformation-Based Postproeessing</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes a hybrid approach to spontaneous speech parsing. The implelnented parser uses an extended probabilistic LR parsing model with rich context and its output is post-processed by a symbolic tree transformation routine that tries to eliminate systematic errors of the parser. The parser has been trained for three different languages and was successflflly integrated in tile Verbmobil speech-to-speech translation system. The parser achieves more than 90%/90% labeled precision/recall on pmsed Verbmobil utterances while 3% of German and 5% of all English input caunot be parsed.</Paragraph>
  </Section>
class="xml-element"></Paper>