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<Paper uid="W02-1603">
  <Title>Plaesarn: Machine-Aided Translation Tool for English-to-Thai Prachya Boonkwan and Asanee Kawtrakul Specialty Research Unit of Natural Language Processing</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
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Abstract
</SectionTitle>
    <Paragraph position="0"> English-Thai MT systems are nowadays restricted by incomplete vocabularies and translation knowledge. Users must consequently accept only one translation result that is sometimes semantically divergent or ungrammatical.</Paragraph>
    <Paragraph position="1"> With the according reason, we propose novel Internet-based translation assistant software in order to facilitate document translation from English to Thai. In this project, we utilize the structural transfer model as the mechanism.</Paragraph>
    <Paragraph position="2"> This project differs from current English-Thai MT systems in the aspects that it empowers the users to manually select the most appropriate translation from every possibility and to manually train new translation rules to the system if itisnecessary. Withtheappliedmodel, weovercome four translation problems--lexicon rearrangement, structural ambiguity, phrase translation, and classifier generation. Finally, we started the system evaluation with 322 randomly selected sentences on the Future Magazine bilingual corpus and the system yielded 59.87% and 83.08% translation accuracy for the best case and the worse case based on 90.1% average precision of the parser.</Paragraph>
    <Paragraph position="3"> Introduction Information comprehension of Thai people should not be only limited in Thai; in contrast, it should also include a considerably large amount of information sources from foreign countries. Insufficient basic language knowledge, a result of inadequate distribution in the past, conversely, is the major obstruction for information comprehension. There are presently several English-Thai MT systems--for instance, Parsit (Sornlertlamvanich, 2000), Plae Thai, and AgentDict. The first one applies semantic transfer model via the methodology similar to the lexical functional grammar (Kaplan et al., 1989) and it is develop with the intention of public use. The latter two implicitly apply the direct transfer model with the purpose of commercial use. Nonetheless, by limited vocabularies and translation rules, the users must accept the only one translation result that is occasionally semantically divergent or ungrammatical. Due to the according reason, we initiated this project in order to relieve language problem of Thai people. In this project, we develop a semi-automatic translation system to assist them to translate English documents into Thai. For this paper, the term semi-automatic translation means the sentence translation with user interaction to manually resolve structural and semantic ambiguities during translation period. Despite manual disambiguation, we provided a simple statistical disambiguation in order to pre-select the most possible translation for each source language sentence, though. The automatic semantic disambiguation can be thus excluded with this approach.</Paragraph>
  </Section>
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