<?xml version="1.0" standalone="yes"?>
<Paper uid="W04-0110">
  <Title>Segment Predictability as a Cue in Word Segmentation: Application to Modern Greek</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Several computational simulations of how children solve the word segmentation problem have been proposed, but most have been applied only to a limited number of languages.</Paragraph>
    <Paragraph position="1"> One model with some experimental support uses distributional statistics of sound sequence predictability (Saffran et al. 1996). However, the experimental design does not fully specify how predictability is best measured or modeled in a simulation. Saffran et al. (1996) assume transitional probability, but Brent (1999a) claims mutual information (MI) is more appropriate. Both assume predictability is measured locally, relative to neighboring segment-pairs.</Paragraph>
    <Paragraph position="2"> This paper replicates Brent's (1999a) mutual-information model on a corpus of child-directed speech in Modern Greek, and introduces a variant model using a global threshold. Brent's finding regarding the superiority of MI is confirmed; the relative performance of local comparisons and global thresholds depends on the evaluation metric.</Paragraph>
  </Section>
class="xml-element"></Paper>