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<Paper uid="W02-2012">
  <Title>GraSp: Grammar learning from unlabelled speech corpora</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Concluding remarks
</SectionTitle>
    <Paragraph position="0"> As far as we know, GraSp is the first published algorithm for extracting grammatical taxonomy out of untagged corpora of spoken language.12 This in an uneasy situation, since if our findings are not comparable to those of other approaches to grammar learning, how could our results be judged [?] or falsified? Important issues wide open to discussion are: validation of results, psycho-linguistic relevance of the experimental setup, principled ways of surpassing the context-free limitations of Lambek grammar (inherited in GraSp), just to mention a few.</Paragraph>
    <Paragraph position="1"> On the other hand, already the spin-offs of our project (the collection of non-linguistic learners) do inspire confidence in our tenets, we 12 The learning experiment sketched in Moortgat (2001) shares some of GraSp's features.</Paragraph>
    <Paragraph position="2"> think - even if the big issue of psychological realism has so far only just been touched.</Paragraph>
    <Paragraph position="3"> The GraSp implementation referred to in this paper is available for test runs at http://www.id.cbs.dk/~pjuel/GraSp</Paragraph>
  </Section>
class="xml-element"></Paper>