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    Comparion of different POS tagging technique (N-Gram, HMM and Brill's tagger) for Bangla

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    Date
    2006
    Publisher
    BRAC University
    Author
    Hasan, Fahim Muhammad
    Naushad UzZaman
    Khan, Mumit
    Metadata
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    URI
    http://hdl.handle.net/10361/625
    Abstract
    There are different approaches to the problem of assigning each word of a text with a parts-of-speech tag, which is known as Part-Of-Speech (POS) tagging. In this paper we compare the performance of a few POS tagging techniques for Bangla language, e.g. statistical approach (n-gram, HMM) and transformation based approach (Brill’s tagger). A supervised POS tagging approach requires a large amount of annotated training corpus to tag properly. At this initial stage of POS-tagging for Bangla, we have very limited resource of annotated corpus. We tried to see which technique maximizes the performance with this limited resource. We also checked the performance for English and tried to conclude how these techniques might perform if we can manage a substantial amount of annotated corpus.
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    Description
    Includes bibliographical references (page 6-7).
    Department
    Center for Research on Bangla Language Processing (CRBLP), BRAC University
    Collections
    • Conference Papers (Centre for Research on Bangla Language Processing)

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