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<Paper uid="P99-1074">
  <Title>Robust, Finite-State Parsing for Spoken Language Understanding</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Human understanding of spoken language appears to integrate the use of contextual expectations with acoustic level perception in a tightly-coupled, sequential fashion. Yet computer speech understanding systems typically pass the transcript produced by a speech recognizer into a natural language parser with no integration of acoustic and grammatical constraints. One reason for this is the complexity of implementing that integration. To address this issue we have created a robust, semantic parser as a single finite-state machine (FSM). As such, its run-time action is less complex than other robust parsers that are based on either chart or generalized left-right (GLR) architectures. Therefore, we believe it is ultimately more amenable to direct integration with a speech decoder.</Paragraph>
  </Section>
class="xml-element"></Paper>