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        <title>Using TERp to Augment the System Combination for SMT</title>
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        <namePart type="given">Jinhua</namePart>
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        <dateIssued>2010-oct&quot; 31-&quot;nov&quot; 4&quot;</dateIssued>
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            <title>Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers</title>
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            <publisher>Association for Machine Translation in the Americas</publisher>
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    <abstract>TER-Plus (TERp) is an extended TER evaluation metric incorporating morphology, synonymy and paraphrases. There are three new edit operations in TERp: Stem Matches, Synonym Matches and Phrase Substitutions (Paraphrases). In this paper, we propose a TERp-based augmented system combination in terms of the backbone selection and consensus decoding network. Combining the new properties of the TERp, we also propose a two-pass decoding strategy for the lattice-based phrase-level confusion network (CN) to generate the final result.The experiments conducted on the NIST2008 Chinese-to-English test set show that our TERp-based augmented system combination framework achieves significant improvements in terms of BLEU and TERp scores compared to the state-of-the-art word-level system combination framework and a TER-based combination strategy.</abstract>
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        <url>https://aclanthology.org/2010.amta-papers.9</url>
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%0 Conference Proceedings
%T Using TERp to Augment the System Combination for SMT
%A Du, Jinhua
%A Way, Andy
%S Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2010
%8 oct" 31 "nov" 4"
%I Association for Machine Translation in the Americas
%C Denver, Colorado, USA
%F du-way-2010-using
%X TER-Plus (TERp) is an extended TER evaluation metric incorporating morphology, synonymy and paraphrases. There are three new edit operations in TERp: Stem Matches, Synonym Matches and Phrase Substitutions (Paraphrases). In this paper, we propose a TERp-based augmented system combination in terms of the backbone selection and consensus decoding network. Combining the new properties of the TERp, we also propose a two-pass decoding strategy for the lattice-based phrase-level confusion network (CN) to generate the final result.The experiments conducted on the NIST2008 Chinese-to-English test set show that our TERp-based augmented system combination framework achieves significant improvements in terms of BLEU and TERp scores compared to the state-of-the-art word-level system combination framework and a TER-based combination strategy.
%U https://aclanthology.org/2010.amta-papers.9

Markdown (Informal)

[Using TERp to Augment the System Combination for SMT](https://aclanthology.org/2010.amta-papers.9) (Du & Way, AMTA 2010)

• Using TERp to Augment the System Combination for SMT (Du & Way, AMTA 2010)

ACL

• Jinhua Du and Andy Way. 2010. Using TERp to Augment the System Combination for SMT. In Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers, Denver, Colorado, USA. Association for Machine Translation in the Americas.