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Phrase based statistic MT (SMT) is an important milestone in MT. However, the translation model in the phrase based SMT is structure free which limits its reordering capacity to some extent. In order to enhance the reordering capacity of phrase based SMT, in this paper we propose a head-modifier relation based reordering model, which exploits the way how to utilize the structured linguistic analysis...
We describe an improved strategy to combine the outputs of machine translation on sentence-level balancing the stability and the effectiveness of the combination. The new method alternates the classical MBR-based sentence-level combination with weighted Minimum Bayes Risk (wMBR). During the calculation of the risk, we weight the hypotheses with the performance of the MT system, which is measured by...
Both classification and ranking strategy have been reported positively in mining the named entity (NE) translation from the snippets re-turned by the Web search engine. Taking the most challenging issue of the organization name and its translation as an example, this paper conducts a contrastive study on the two strategies under SVM framework. We empirically show that the method of translation ranking...
Human evaluation of translation involves many aspects. In this paper we try to make some quantitative analyses on factors influencing translation scores generated by human. We focus on some linguistic features especially some translation error types which may affect human evaluation. The experiment shows that the inconsistency in thematic knowledge and the semantic incoherence in target text have...
Machine transliteration is to translate the proper nouns in the source language according to its pronunciation into the target language. Recent orthographical based approach has improved the performance of machine translation significantly. Focusing on the transliteration unit alignment that provides a fundamental parameter for the model, this paper adopts a semi-supervised EMD approach-applying discriminative...
BLEU is one of the most popular metrics for automatic evaluation of machine translation quality. Focusing on its ignorance of different effects of various translation units upon translation quality, this paper extends proper weights to different words and n-grams in the framework of BLEU. The linear regression method is adopted to capture the human perception on translation quality via word types...
This paper proposes a method of domain sensitive example based machine translation system between Chinese and English. First, the example base is automatically extracted according to the relative position of word alignments, which is a language independent approach. Then, through combining the text-classification technique, the EBMT system manages to select the most appropriate example base for the...
For improving the effectiveness of cross-lingual information retrieval (CLIR), a domain ontology knowledge based method is presented to apply to C-E CLIR. In this study, the domain ontology knowledge is acquired from both source language user queries and target documents to select target translation and re-rank initial retrieval documents set. The C-E CLIR dataset from NTCIR-4 Workshop is used to...
Improved approach of phrase extraction was proposed for phrase-based statistical machine translation. The effectiveness was investigated when using n-best alignments instead of one-best for phrase extraction. Bilingual phrase pairs were extracted in the presented approach by combining word-to-word links from n-best alignments between source and target sentences. First, the n-best alignments were divided...
Automatic acquisition of translation templates is important for MT system to improve its translation quality and its ability of adaptation to new domain. In this paper, translation equivalences are obtained from translation corresponding trees of bilingual sentence pairs. Error-driven learning method is employed to acquire templates from extracted equivalences. At the same time, optimization method...
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