Combined word alignments

Tufiș, Dan; Ion, Radu; Ceauşu, Alexandru; Ştefănescu, Dan

doi:10.3115/1654449.1654470

Cited by 7 publications

(2 citation statements)

References 10 publications

(9 reference statements)

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“…This task focused on languages with scarce resources. For the subtask of unlimited resources, some researchers (Aswani and Gaizauskas, 2005;Lopez and Resnik, 2005;Tufis et al, 2005) used language-dependent resources such as dictionary, thesaurus, and dependency parser to improve word alignment results.…”

Section: Related Workmentioning

confidence: 99%

Pivot language approach for phrase-based statistical machine translation

Wu¹,

Wang²

2007

Machine Translation

137

131

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This paper proposes a novel method for phrase-based statistical machine translation based on the use of a pivot language. To translate between languages L s and L t with limited bilingual resources, we bring in a third language, L p , called the pivot language. For the language pairs L s − L p and L p − L t , there exist large bilingual corpora. Using only L s − L p and L p − L t bilingual corpora, we can build a translation model for L s − L t . The advantage of this method lies in the fact that we can perform translation between L s and L t even if there is no bilingual corpus available for this language pair. Using BLEU as a metric, our pivot language approach significantly outperforms the standard model trained on a small bilingual corpus. Moreover, with a small L s − L t bilingual corpus available, our method can further improve translation quality by using the additional L s − L p and L p − L t bilingual corpora.

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Section: Related Workmentioning

confidence: 99%

Pivot language approach for phrase-based statistical machine translation

Wu¹,

Wang²

2007

Machine Translation

137

131

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“…Martin et al (2005) reported that this method resulted in absolute improvements of up to 20% as compared with the case of only using limited resources. Tufis et al (2005) combined two word aligners: one is based on the limited resources and the other is based on the unlimited resources. The unlimited resource consists of a translation dictionary extracted from the alignment of Romanian and English WordNet.…”

Section: Related Workmentioning

confidence: 99%

Word alignment for languages with scarce resources using bilingual corpora of other language pairs

Wang¹,

Wu²,

Liu³

2006

Proceedings of the COLING/ACL on Main Conference Poster Sessions -

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This paper proposes an approach to improve word alignment for languages with scarce resources using bilingual corpora of other language pairs. To perform word alignment between languages L1 and L2, we introduce a third language L3. Although only small amounts of bilingual data are available for the desired language pair L1-L2, large-scale bilingual corpora in L1-L3 and L2-L3 are available. Based on these two additional corpora and with L3 as the pivot language, we build a word alignment model for L1 and L2. This approach can build a word alignment model for two languages even if no bilingual corpus is available in this language pair. In addition, we build another word alignment model for L1 and L2 using the small L1-L2 bilingual corpus. Then we interpolate the above two models to further improve word alignment between L1 and L2. Experimental results indicate a relative error rate reduction of 21.30% as compared with the method only using the small bilingual corpus in L1 and L2.

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