Incorporating source-language paraphrases into phrase-based SMT with confusion networks
Jiang, Jie and Du, Jinhua and Way, Andy (2011) Incorporating source-language paraphrases into phrase-based SMT with confusion networks. In: SSST-2011: The Fifth Workshop on Syntax and Structure in Statistical Translation , 23 June 2011, Portland, Oregon, USA.
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To increase the model coverage, sourcelanguage paraphrases have been utilized to boost SMT system performance. Previous
work showed that word lattices constructed from paraphrases are able to reduce out-ofvocabulary words and to express inputs in different ways for better translation quality.
However, such a word-lattice-based method suffers from two problems: 1) path duplications in word lattices decrease the capacities for potential paraphrases; 2) lattice decoding in SMT dramatically increases the search space and results in poor time efﬁciency. Therefore, in this paper, we adopt word confusion networks as the input structure to carry source-language paraphrase information. Similar to previous work, we use word lattices to build word confusion networks for merging of duplicated paths and faster decoding. Experiments are carried out on small-, medium- and large-scale English–
Chinese translation tasks, and we show that compared with the word-lattice-based method, the decoding time on three tasks is reduced signiﬁcantly (up to 79%) while comparable
translation quality is obtained on the largescale task.
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