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<Paper uid="P98-2141">
  <Title>Simultaneous Interpretation Utilizing Example-based Incremental Transfer</Title>
  <Section position="5" start_page="859" end_page="860" type="concl">
    <SectionTitle>
5 Related Research
</SectionTitle>
    <Paragraph position="0"> Several schemes have been proposed with respect to incremental translation based on the synchronization of input and output fragments and the use of specialized information for simultaneous interpretation. (Kitano, 1994) proposes incremental translation that is based on marker-passing memory-based translation. Although the technique adopts a cost-oriented best-first strategy to avoid the explosion of structural ambiguity, the strategy does not pay attention to actual aspects of the overall meaning such as in the case when a previously made assumption turns out to be incorrect. (Matsubara, 1997) proposed a method to handle extra- null grammatical phenomena with a chart-based incremental English-Japanese MT system based on observations of a translation corpus. However, this system was only capable of English to Japanese translation. In this paper, the aspects of flexible order, repetitions, and ellipses are only briefly considered and necessary extensions, such as the adjustment of consistency in related to the whole sentence by employing simultaneous interpreters' &amp;quot;knowledge have not been previously investigated.</Paragraph>
    <Paragraph position="1"> Conclusion We have described a practical method of automatic simultaneous interpretation. In the exploitation of empirical knowledge, we examined the kind of empirical knowledge required to achieve efficient simultaneous interpretation. We then have proposed a method to exploit these empirical simultaneous translation examples in an example-based framework to produce a practical method of simultaneous interpretation.</Paragraph>
    <Paragraph position="2"> Preliminary experimentation analyzing our proposed scheme showed that it can be utilized to achieve a simultaneous interpretation system.</Paragraph>
    <Paragraph position="3"> The possibility of applying this sort of example-based framework into multilingual translation, such as a Japanese-German pair and a Japanese-Korean pair, has been shown in (Furuse, 1995) and (Mima, 1997). Therefore, the algorithm can also be expected to work for not only an English-Japanese pair but also other language pairs.</Paragraph>
    <Paragraph position="4"> Important areas of future research will involve methods for: * Predicting the contents of the next utterance by using dialog-specific discourse analysis (Levin, 1995) * Handling linguistic differences between the source and target languages such as subject ellipsis We believe that some situational information, such as the speakers-roles in the conversation (Mima, 1997) could be potentially helpful for both predicting the contents of the next utterance and resolving linguistic differences. The integration of statistical/stochastic approaches, such as Decision-Tree Learning (Yamamoto, 1997) for the above discourse-related issues is another area of interest for future work.</Paragraph>
  </Section>
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