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<Paper uid="W06-1646">
  <Title>Corrective Models for Speech Recognition of Inflected Languages</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper presents a corrective model for speech recognition of inflected languages. The model, based on a discriminative framework, incorporates word n-grams features as well as factored morphological features, providing error reduction over the model based solely on word n-gram features. Experiments on a large vocabulary task, namely the Czech portion of the MALACH corpus, demonstrate performance gain of about 1.1-1.5% absolute in word error rate, wherein morphological features contribute about a third of the improvement. A simple feature selection mechanism based on kh2 statistics is shown to be effective in reducing the number of features by about 70% without any loss in performance, making it feasible to explore yet larger feature spaces.</Paragraph>
  </Section>
class="xml-element"></Paper>