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<Paper uid="C94-2147">
  <Title>Table-driven Neural Syntactic Analysis of Spoken Korean</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1. Introduction
</SectionTitle>
    <Paragraph position="0"> Spoken language input may be one of the most preferred interface with computer systems if speech can be well integrated with the natural language processing.</Paragraph>
    <Paragraph position="1"> There have been a few attempts to integrate speech recognition with Ihe natural language understanding. (Hayes 1986) adopted the case frame instantiation technique to parse continuously spoken English sentences given in the form of a word lattice (a set of word candidates hypothesized by a speech recognition module) and t)roduced a frame representation of the tltterence.</Paragraph>
    <Paragraph position="2"> (Pocsio 1987) suggested a modified caseframc parsing to parse a word latlice in Italian. (Lee,, L. S. 1987) developed a prototype Chinese (Mandarin) dictation machine which takes a syllable lattice and produces a Chinese character sequence. (Saito 1991) used GLR technique to parse a sequence of Japanese phonenms and, integrated wilh the tlMM technique, developed a HMM-I.R parser (Kita 1991).</Paragraph>
    <Paragraph position="3"> lh)wever, spoken Korean has many distinguished characteristics compared with spoken English and even with spoken Japanese, for example, comlpex word formation, phonological changes and irregular conjugations. In this paper, we present a CYK-table driven interactive relaxation parsing method of spoken Korean, integrated with the CYK-based inorphological analysis. A Korean phoneme lattice is assumed as input and the CYK-based morphological analysis copes with the difficulties of complex word formation, phonological changes and irregular conjugations. Categorial Gralnmar is adapted and extended to treat the free word-order in Korean and the CYK-tablc driven interactive relaxation parsing gives et'ficicncy beyond the general interactive relaxation parsing methods such as (Howclls t988; Nijholt 1990).</Paragraph>
  </Section>
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