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Unsupervised Segmentation for Different Types of Morphological Processes Using Multiple Sequence Alignment

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Statistical Language and Speech Processing (SLSP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7978))

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Abstract

The aim of unsupervised and knowledge free morphological segmentation is the identification of boundaries between morphs in words of a given language without relying on any knowledge source about that language. This paper describes a segmentation method that draws on previous approaches based both on semantic and orthographical similarity to identify morphologically related words. Using a version of Multiple Sequence Alignment originally applied in bioinformatics, the method extracts both concatenative and non-concatenative (e.g. introflection and circumfixation) morphological patterns and can thus handle languages of different morphological types as well as non-dominant morphological processes within languages of a particular predominant morphological type.

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Author information

Authors and Affiliations

  1. Department for Natural Language Processing, University of Leipzig, Augustusplatz 10, D-04109, Leipzig, Germany

    Amit Kirschenbaum

Authors
  1. Amit Kirschenbaum
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Editor information

Editors and Affiliations

  1. Research Group on Mathematical Linguistics, Universitat Rovira i Virgili, Avinguda Catalunya, 35, 43002, Tarragona, Spain

    Adrian-Horia Dediu  & Carlos Martín-Vide  & 

  2. Research Institute for Information and Language Processing, Research Group in Computational Linguistics, University of Wolverhampton, WV1 1SB, Wolverhampton, UK

    Ruslan Mitkov

  3. Fakultät für Informatik, Institut für Wissens- und Sprachverarbeitung, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Bianca Truthe

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Kirschenbaum, A. (2013). Unsupervised Segmentation for Different Types of Morphological Processes Using Multiple Sequence Alignment. In: Dediu, AH., Martín-Vide, C., Mitkov, R., Truthe, B. (eds) Statistical Language and Speech Processing. SLSP 2013. Lecture Notes in Computer Science(), vol 7978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39593-2_14

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  • DOI: https://doi.org/10.1007/978-3-642-39593-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39592-5

  • Online ISBN: 978-3-642-39593-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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