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        <title>A statistical view on bilingual lexicon extraction</title>
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        <namePart type="given">Pascale</namePart>
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            <title>Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers</title>
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        <name type="personal">
            <namePart type="given">David</namePart>
            <namePart type="family">Farwell</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Laurie</namePart>
            <namePart type="family">Gerber</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Eduard</namePart>
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    <abstract>We present two problems for statistically extracting bilingual lexicon: (1) How can noisy parallel corpora be used? (2) How can non-parallel yet comparable corpora be used? We describe our own work and contribution in relaxing the constraint of using only clean parallel corpora. DKvec is a method for extracting bilingual lexicons, from noisy parallel corpora based on arrival distances of words in noisy parallel corpora. Using DKvec on noisy parallel corpora in English/Japanese and English/Chinese, our evaluations show a 55.35% precision from a small corpus and 89.93% precision from a larger corpus. Our major contribution is in the extraction of bilingual lexicon from non-parallel corpora. We present a first such result in this area, from a new method-Convec. Convec is based on context information of a word to be translated.</abstract>
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        <date>1998-oct 28-31</date>
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%0 Conference Proceedings
%T A statistical view on bilingual lexicon extraction
%A Fung, Pascale
%Y Farwell, David
%Y Gerber, Laurie
%Y Hovy, Eduard
%S Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers
%D 1998
%8 oct 28 31
%I Springer
%C Langhorne, PA, USA
%F fung-1998-statistical
%X We present two problems for statistically extracting bilingual lexicon: (1) How can noisy parallel corpora be used? (2) How can non-parallel yet comparable corpora be used? We describe our own work and contribution in relaxing the constraint of using only clean parallel corpora. DKvec is a method for extracting bilingual lexicons, from noisy parallel corpora based on arrival distances of words in noisy parallel corpora. Using DKvec on noisy parallel corpora in English/Japanese and English/Chinese, our evaluations show a 55.35% precision from a small corpus and 89.93% precision from a larger corpus. Our major contribution is in the extraction of bilingual lexicon from non-parallel corpora. We present a first such result in this area, from a new method-Convec. Convec is based on context information of a word to be translated.
%U https://link.springer.com/chapter/10.1007/3-540-49478-2_1
%P 1-17

Markdown (Informal)

[A statistical view on bilingual lexicon extraction](https://link.springer.com/chapter/10.1007/3-540-49478-2_1) (Fung, AMTA 1998)

• A statistical view on bilingual lexicon extraction (Fung, AMTA 1998)

ACL

• Pascale Fung. 1998. A statistical view on bilingual lexicon extraction. In Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 1–17, Langhorne, PA, USA. Springer.