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    » Using Random Forests in the Structured Language Model
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    ICPR
    2006
    IEEE
    192views computer vision» more  ICPR 2006»
    Detecting Coarticulation in Sign Language using Conditional Random Fields
    16 years 5 months ago
    Detecting Coarticulation in Sign Language using Conditional Random Fields
    Download  marathon.csee.usf.edu
    Coarticulation is one of the important factors that makes automatic sign language recognition a hard problem. Unlike in speech recognition, coarticulation effects in sign language...
    Ruiduo Yang, Sudeep Sarkar
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    134
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    ACL
    2008
    112views Computational Linguistics» more  ACL 2008»
    Efficient Multi-Pass Decoding for Synchronous Context Free Grammars
    15 years 5 months ago
    Efficient Multi-Pass Decoding for Synchronous Context Free Grammars
    Download  www.cs.rochester.edu
    We take a multi-pass approach to machine translation decoding when using synchronous context-free grammars as the translation model and n-gram language models: the first pass uses...
    Hao Zhang, Daniel Gildea
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    170
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    ACL
    2004
    198views Computational Linguistics» more  ACL 2004»
    Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
    15 years 5 months ago
    Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
    Download  www.aclweb.org
    This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
    Brian Roark, Murat Saraclar, Michael Collins, Mark...
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    97
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    EACL
    2009
    ACL Anthology
    98views Natural Language Processing» more  EACL 2009»
    An Alignment Algorithm Using Belief Propagation and a Structure-Based Distortion Model
    16 years 4 months ago
    An Alignment Algorithm Using Belief Propagation and a Structure-Based Distortion Model
    Download  aclweb.org
    Fabien Cromierès, Sadao Kurohashi
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    AAAI
    2010
    186views Intelligent Agents» more  AAAI 2010»
    Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships
    15 years 4 months ago
    Fast Conditional Density Estimation for Quantitative Structure-Activity Relationships
    Download  wwwkramer.in.tum.de
    Many methods for quantitative structure-activity relationships (QSARs) deliver point estimates only, without quantifying the uncertainty inherent in the prediction. One way to qua...
    Fabian Buchwald, Tobias Girschick, Eibe Frank, Ste...
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