W07-0733 data to speed up the GIZA + + word alignment process . Traditionally , we worked with
P10-1085 probabilities into the bidirectional word alignment process . Given alignment sets and .
N09-1015 phrase table is errors from the word alignment process . For exam - ple , many function
W05-0808 the first three stages of the word alignment process , many words remain unaligned
P11-2051 comparing to the baseline corpus . The word alignment process using generative models is more
P11-1042 constructed using standard generative word alignment processes . 7 Future Work While we have
P06-2092 analyses to guide and restrict the word alignment process . The advantage of using available
S10-1003 that results from the automated word alignment process ( GIZA + + ) . 2 . For the Out-of-five
D12-1123 information into WTM to constrain the word alignment process , in order to identify opinion
W09-2906 are grouped together before the word alignment process . This will increase both the
W08-0509 GIZA + + that accelerate this word alignment process . One of the implementations
P14-1030 opinion relations as a monolingual word alignment process . Each opinion target can find
W08-0409 syntactic dependencies into the word alignment process is shown in Table 4 . Syntax
D14-1060 employ three models that enable word alignment process to leverage topical contents
P14-2075 to errors in the sentence and word alignment processes , not all words that are aligned
J10-3003 do serve to counter the noisy word alignment process , they do so only to a degree
E12-1010 level , then the output of the word alignment process is used to identify and align
W03-0304 into the statistical translation word alignment process leads to better alignments .
W08-1403 The Uplug system implements a word alignment process that combines different statistical
W08-1403 crucial preprocessing step for the word alignment process , and a lot of the sentence parallel
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