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    ACL
    2006
    91views Computational Linguistics» more  ACL 2006»
    Extracting Loanwords from Mongolian Corpora and Producing a Japanese-Mongolian Bilingual Dictionary
    15 years 5 months ago
    Extracting Loanwords from Mongolian Corpora and Producing a Japanese-Mongolian Bilingual Dictionary
    Download  www.cl.cs.titech.ac.jp
    This paper proposes methods for extracting loanwords from Cyrillic Mongolian corpora and producing a Japanese
    Badam-Osor Khaltar, Atsushi Fujii, Tetsuya Ishikaw...
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    ACL
    2001
    104views Computational Linguistics» more  ACL 2001»
    Empirically Estimating Order Constraints for Content Planning in Generation
    15 years 5 months ago
    Empirically Estimating Order Constraints for Content Planning in Generation
    Download  acl.ldc.upenn.edu
    In a language generation system, a content planner embodies one or more "plans" that are usually hand
    Pablo Ariel Duboué, Kathleen McKeown
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    ACL
    2003
    76views Computational Linguistics» more  ACL 2003»
    A SNoW Based Supertagger with Application to NP Chunking
    15 years 5 months ago
    A SNoW Based Supertagger with Application to NP Chunking
    Download  acl.ldc.upenn.edu
    Supertagging is the tagging process of assigning the correct elementary tree of LTAG, or the correct supertag, to each
    Libin Shen, Aravind K. Joshi
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    ACL
    2003
    108views Computational Linguistics» more  ACL 2003»
    A Prototype Text to British Sign Language (BSL) Translation System
    15 years 5 months ago
    A Prototype Text to British Sign Language (BSL) Translation System
    Download  acl.ldc.upenn.edu
    We demonstrate a text to sign language translation system for investigating sign language (SL) structure and assisting in production of sign narratives and informa
    Ian Marshall, Éva Sáfár
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    ACL
    1997
    95views Computational Linguistics» more  ACL 1997»
    Mistake-Driven Mixture of Hierarchical Tag Context Trees
    15 years 5 months ago
    Mistake-Driven Mixture of Hierarchical Tag Context Trees
    Download  www.aclweb.org
    This paper proposes a mistake-driven mixture method for learning a tag model. The method iteratively performs two proce
    Masahiko Haruno, Yuji Matsumoto
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