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    COLING
    2002
    100views Computational Linguistics» more  COLING 2002»
    A Robust Cross-Style Bilingual Sentences Alignment Model
    13 years 7 months ago
    A Robust Cross-Style Bilingual Sentences Alignment Model
    Download  acl.ldc.upenn.edu
    Most current sentence alignment approaches adopt sentence length and cognate as the alignment features; and they are mostly trained and tested in the documents with the same style...
    Tz-Liang Kueng, Keh-Yih Su
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    IVC
    2008
    83views more  IVC 2008»
    A minimum description length objective function for groupwise non-rigid image registration
    13 years 7 months ago
    A minimum description length objective function for groupwise non-rigid image registration
    Download  www-ist.massey.ac.nz
    Groupwise non-rigid registration aims to find a dense correspondence across a set of images, so that analogous structures in the images are aligned. For purely automatic inter-sub...
    Stephen Marsland, Carole J. Twining, Christopher J...
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    NAACL
    2004
    98views Computational Linguistics» more  NAACL 2004»
    Minimum Bayes-Risk Decoding for Statistical Machine Translation
    13 years 9 months ago
    Minimum Bayes-Risk Decoding for Statistical Machine Translation
    Download  acl.ldc.upenn.edu
    We present Minimum Bayes-Risk (MBR) decoding for statistical machine translation. This statistical approach aims to minimize expected loss of translation errors under loss functio...
    Shankar Kumar, William J. Byrne
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    EACL
    2009
    ACL Anthology
    213views Natural Language Processing» more  EACL 2009»
    N-Gram-Based Statistical Machine Translation versus Syntax Augmented Machine Translation: Comparison and System Combination
    14 years 8 months ago
    N-Gram-Based Statistical Machine Translation versus Syntax Augmented Machine Translation: Comparison and System Combination
    Download  gps-tsc.upc.es
    In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Syntax Augmented Machine Translation system (SAMT) and UPC-TALP N-gram-based Statisti...
    José A. R. Fonollosa, Maxim Khalilov
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    EMNLP
    2008
    131views Natural Language Processing» more  EMNLP 2008»
    Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation
    13 years 9 months ago
    Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation
    Download  www.aclweb.org
    This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual info...
    Qun Liu, Zhongjun He, Yang Liu, Shouxun Lin
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