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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Pre-processing of Bilingual Corpora for Mandarin-English EBMT Ying Zhang; Ralf Brown; Robert Frederking... In: http://pepperoni.is.cs.cmu.edu/research/public/publications/mtSummitVIII.ps (2001) BASE Show details 2 Pre-processing of Bilingual Corpora for Mandarin-English EBMT Ying Zhang; Ralf Brown; Robert Frederking... In: http://projectile.is.cs.cmu.edu/research/public/publications/mtSummitVIII.pdf BASE Show details 3 Pre-processing of Bilingual Corpora for Mandarin-English EBMT Ying Zhang; Ralf Brown; Robert Frederking... In: http://www.eamt.org/events/summitVIII/papers/zhang.pdf BASE Show details 4 Pre-processing of Bilingual Corpora for Mandarin-English EBMT Ying Zhang; Ralf Brown; Robert Frederking; Alon Lavie In: http://www.mt-archive.info/MTS-2001-Zhang.pdf Abstract: Pre-processing of bilingual corpora plays an important role in Example-Based Machine Translation (EBMT) and Statistical-Based Machine Translation (SBMT). For our Mandarin-English EBMT system, pre-processing includes segmentation for Mandarin, bracketing for English and building a statistical dictionary from the corpora. We used the Mandarin segmenter from the Linguistic Data Consortium (LDC). It uses dynamic programming with a frequency dictionary to segment the text. Although the frequency dictionary is large, it does not completely cover the corpora. In this paper, we describe the work we have done to improve the segmentation for Mandarin and the bracketing process for English to increase the length of English phrases. A statistical dictionary is built from the aligned bilingual corpus. It is used as feedback to segmentation and bracketing to re-segment / re-bracket the corpus. The process iterates several times to achieve better results. The final results of the corpus pre-processing are a segmented/bracketed aligned bilingual corpus and a statistical dictionary. We achieved positive results by increasing the average length of Chinese terms about 60 % and 10 % for English. The statistical dictionary gained about a 30 % increase in coverage. Keyword: Bilingual corpus; bilingual segmentation/bracketing; pre-processing; tokenization URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.513.3844 http://www.mt-archive.info/MTS-2001-Zhang.pdf BASE Hide details

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