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<Paper uid="H93-1078">
  <Title>Gisting Continuous Speech</Title>
  <Section position="1" start_page="0" end_page="0" type="metho">
    <SectionTitle>
PROJECT GOALS
</SectionTitle>
    <Paragraph position="0"> The objective of this work is automatic, real-time &amp;quot;gisting&amp;quot; of voice: traffic for updating of information in databases, for producing timely reports, and for prompt notification of events of interest. Specifically, the goal is to build a prototype, real-time system capable of processing radio communication between air traffic controllers and pilots; identifying dialogs and extracting their &amp;quot;gist&amp;quot; (e.g., identifying flights, determining whether they are landing or taking off), and producing a continuous output stream with that information.</Paragraph>
    <Paragraph position="1"> The approach is intended to be general and applicable to other domains.</Paragraph>
    <Paragraph position="2"> The system is built upon state-of-the-art techniques in speech recognition, speaker identification, natural language analysis, and topic statistical classification. These techniques have been extended where necessary to address specific aspects of the gisting problem. Because various sources of information must be combined, the system design features a itigh degree of interaction between the natural language and domain-knowledge components and the speech processing components.</Paragraph>
  </Section>
  <Section position="2" start_page="0" end_page="0" type="metho">
    <SectionTitle>
RECENT RESULTS
</SectionTitle>
    <Paragraph position="0"> We have made additions and modifications to our prototype system \[1\]. The primary goal of the effort was to achieve real-time performance. This involved both system architectural and algorithmic modifications described fully in \[2\]. A prototype system has been evaluated using approximately 14 hours of data recorded at Logan airport. Performance was measured on appro~nately four hours of data held out for final evaluation. On that data, the system achieved approximately 88% recall and 82% precision for detection of controller-pilot dialogs. Also, of the flights correctly detected, the fight identification was correctly extracted 59% of the time.</Paragraph>
    <Paragraph position="1"> A real-time prototype system has been constructed. The system builds on a flexible software system developed as part of this effort. The system allows multiple processes to be coordinated across multiple hosts and provides facilities for efficient stream connections between modules as well as flexible message-based communication between modules.</Paragraph>
  </Section>
  <Section position="3" start_page="0" end_page="0" type="metho">
    <SectionTitle>
PLANS FOR THE COMING YEAR
</SectionTitle>
    <Paragraph position="0"> The remainder of the effort will focus on completion of the prototype system and on system testing. System testing includes investigation of the sensitivity of overall system performance to the performance of various component.</Paragraph>
  </Section>
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