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<Paper uid="W03-0706">
  <Title>The Pragmatics of Taking a Spoken Language System Out of the Laboratory</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
2 Architecture
</SectionTitle>
    <Paragraph position="0"> The LCS Spoken Language systems use the Galaxy architecture (Seneff et al., 1999). This Galaxy architecture consists of a central hub and servers. Each of the servers performs a specific function, such as converting audio speech into a text translation of that speech or combining the user's past statements with what was said most recently. The individual servers exchange information by sending messages through the hub. These messages contain information to be sent to other servers as well as information used to determine what server or servers should be contacted next.</Paragraph>
    <Paragraph position="1"> Various Galaxy Servers work together to develop a semantic understanding of the user's statements and questions. The sound spoken into the microphone, telephone, or radio is collected by an Audio Server and sent on to the recognizer. The recognizer translates this wave file into text, which is sent to a natural language parser. The parser converts the text into a semantic frame, a representation of the statement's meaning. This meaning representation is passed on to another server, the Dialogue Manager. This server monitors the current context of a conversation and, based on this context, can prompt the user for any necessary clarification and present intelligent responses to the user. Since the Dialogue Manager is aware of what information has been discussed thus far, it is able to determine what information is still needed. A semantic frame is created by the Dialogue Manager and this is sent through the Language Generation Server to generate a text response. The text response is then spoken to the user through a speech synthesis server.</Paragraph>
    <Paragraph position="2"> To solve the problem of retrieving or placing data from/in remote and local sources, we gave the systems below the use of mobile software agents. If userrequested information is not immediately available, an agent can monitor the data sources until it is possible to respond. Users may request a notification or alert when a particular activity occurs, which may happen at an indeterminate time in the future. Because of the potentially significant time lag, it is important to manage dialogue activity so that the user is only interrupted when the need for information is more important than the current task that the user is currently undertaking. This active management of interruptions aids task management and lightens cognitive load (Daniels et al., 2002).</Paragraph>
  </Section>
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