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<Paper uid="W97-0404">
  <Title>Correct parts extraction from speech recognition results using semantic distance calculation, and its application to speech translation</Title>
  <Section position="7" start_page="29" end_page="29" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper proposed a method for extractlag correct parts from speech recognition resuits in order to understand recognition results from speech inputs which may include erroneous parts. Correct parts are extracted using (a) the semantic distances between the input expression and an example expression and (b) the structure selected by the shortest semantic distance.</Paragraph>
    <Paragraph position="1"> We examined three things: (1) the correct parts extraction rate, (2) the effectiveness of the method in improving the speech understanding rate. and (3) the effectiveness of the method in improving the speech translation rate. Results showed that the proposed method is able to efficiently extract the correct parts from speech recognition results; ninety-six percent of the extracted parts are correct. The results also showed that the proposed method is effective in preventing the misunderstanding of the erroneous sentences and in improving the speech translation results. The misunderstanding rate for erroneous sentences is reduced over half and sixty-nine percent of the speech translation results can be improved for misrecognized sentences. null In the future, we will try to feed the extraction results back into the speech recognition process for re-recognizing only the non-extracted parts and to improve the speech recognition performance. By repeating the correct parts extraction and the feedback, we will confirm whether there is an improvement in the understanding and translation performance. Furthermore. we will confirm the effectiveness of the proposed method using other languages.</Paragraph>
  </Section>
class="xml-element"></Paper>