The performance of a machine translation system heavily depends on the quantity and quality of the bilingual language resource. However,getting a parallel corpus,which has a large scale and is of high quality,is a ver...The performance of a machine translation system heavily depends on the quantity and quality of the bilingual language resource. However,getting a parallel corpus,which has a large scale and is of high quality,is a very difficult task especially for low resource languages such as Chinese-Vietnamese. Fortunately,multilingual user generated contents（ UGC）,such as bilingual movie subtitles,provide us access to automatic construction of the parallel corpus. Although the amount of UGC parallel corpora can be considerable,the original corpus is not suitable for statistical machine translation（ SMT） systems. The corpus may contain translation errors,sentence mismatching,free translations,etc. To improve the quality of the bilingual corpus for SMT systems,three filtering methods are proposed： sentence length difference,the semantic of sentence pairs,and machine learning. Experiments are conducted on the Chinese to Vietnamese translation corpus.Experimental results demonstrate that all the three methods effectively improve the corpus quality,and the machine translation performance（ BLEU score） can be improved by 1. 32.展开更多
Statistical machine translation for low-resource language suffers from the lack of abundant training corpora. Several methods, such as the use of a pivot language, have been proposed as a bridge to translate from one ...Statistical machine translation for low-resource language suffers from the lack of abundant training corpora. Several methods, such as the use of a pivot language, have been proposed as a bridge to translate from one language to another. However, errors will accumulate during the extensive translation pipelines. In this paper, we propose an approach to low-resource language translation by exploiting the pronunciation correlations between languages. We find that the pronunciation features can improve both Chinese-Vietnamese and Vietnamese- Chinese translation qualities. Experimental results show that our proposed model yields effective improvements, and the translation performance （bilingual evaluation understudy score） is improved by a maximum value of 1.03.展开更多
Sign language is a visual-gestural language mainly used by hearingimpaired people to communicate with each other. Gesture and facial expression are important grammar parts of sign language. In this paper, a text-base...Sign language is a visual-gestural language mainly used by hearingimpaired people to communicate with each other. Gesture and facial expression are important grammar parts of sign language. In this paper, a text-based transformation method of Chinese-Chinese sign language machine translation is proposed. Gesture and facial expression models are created. And a practical system is implemented. The input of the system is Chinese text. The output of the system is 'graphics person' who can gesticulate Chinese sign language accompanied by facial expression that corresponds to the Chinese text entered so as to realize automatic translation from Chinese text to Chinese sign language.展开更多
基金Supported by the National Basic Research Program of China(973Program)(2013CB329303)the National Natural Science Foundation of China(61502035)
文摘The performance of a machine translation system heavily depends on the quantity and quality of the bilingual language resource. However,getting a parallel corpus,which has a large scale and is of high quality,is a very difficult task especially for low resource languages such as Chinese-Vietnamese. Fortunately,multilingual user generated contents（ UGC）,such as bilingual movie subtitles,provide us access to automatic construction of the parallel corpus. Although the amount of UGC parallel corpora can be considerable,the original corpus is not suitable for statistical machine translation（ SMT） systems. The corpus may contain translation errors,sentence mismatching,free translations,etc. To improve the quality of the bilingual corpus for SMT systems,three filtering methods are proposed： sentence length difference,the semantic of sentence pairs,and machine learning. Experiments are conducted on the Chinese to Vietnamese translation corpus.Experimental results demonstrate that all the three methods effectively improve the corpus quality,and the machine translation performance（ BLEU score） can be improved by 1. 32.
基金supported by the National key Basic Research and Development(973)Program of China(No.2013CB329303)the National Natural Science Foundation of China(Nos.61502035,61132009,and 61671064)Beijing Advanced Innovation Center for Imaging Technology(No.BAICIT-2016007)
文摘Statistical machine translation for low-resource language suffers from the lack of abundant training corpora. Several methods, such as the use of a pivot language, have been proposed as a bridge to translate from one language to another. However, errors will accumulate during the extensive translation pipelines. In this paper, we propose an approach to low-resource language translation by exploiting the pronunciation correlations between languages. We find that the pronunciation features can improve both Chinese-Vietnamese and Vietnamese- Chinese translation qualities. Experimental results show that our proposed model yields effective improvements, and the translation performance （bilingual evaluation understudy score） is improved by a maximum value of 1.03.
文摘Sign language is a visual-gestural language mainly used by hearingimpaired people to communicate with each other. Gesture and facial expression are important grammar parts of sign language. In this paper, a text-based transformation method of Chinese-Chinese sign language machine translation is proposed. Gesture and facial expression models are created. And a practical system is implemented. The input of the system is Chinese text. The output of the system is 'graphics person' who can gesticulate Chinese sign language accompanied by facial expression that corresponds to the Chinese text entered so as to realize automatic translation from Chinese text to Chinese sign language.
