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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="5" start_page="0" end_page="0" type="evalu">
    <SectionTitle>
4 Evaluation
</SectionTitle>
    <Paragraph position="0"> We established the system evaluation on the Future Magazine bilingual corpus. We categorized the evaluation into two environments--under restricted knowledge base and under increasing knowledge base. Each of which is also categorized into two environments--with parsing errors and without parsing errors.</Paragraph>
    <Paragraph position="1"> In the evaluation, we randomly selected 322 sentences from the corpus. In order to have a manageable task and facilitate performance measurement, we classify translation result into the following three categories--exact (the same as in the corpus), moderate (understandable result), and incomprehensible (obviously nonunderstandable result). Table 5 shows the evaluation results.</Paragraph>
    <Paragraph position="2"> In this evaluation, we consider the results in the exact and moderate categories as reason- null The column A represents evaluation with restricted knowledge base and with parsing errors, B as with restricted knowledge base but without parsing errors, C as with increasing knowledge base but with parsing errors, and D as with increasing knowledge base and without parsing errors.  able translations. Moreover, we also consider that the evaluation with restricted knowledge base and with parsing errors is the worst case performance, and the evaluation with increasing knowledge base and without parsing errors is the best case performance.</Paragraph>
    <Paragraph position="3"> Fromtheconstraintsweestablished, wefound that the system yielded the translation accuracy for 59.87% for the worst case and 83.08% for the best case.</Paragraph>
  </Section>
class="xml-element"></Paper>