Conversion refers to the transformation of parts of speech in some words while maintaining the original content unchanged in order to make the translated text sound smooth and fluent as well as more idiomatic in the t...Conversion refers to the transformation of parts of speech in some words while maintaining the original content unchanged in order to make the translated text sound smooth and fluent as well as more idiomatic in the target language. In E-C translation, conversion of pars of speech is one of the most important translation methods. Several different forms about conversion of parts of speech are introduced through analyzing the differences and usages between the two languages so that a better version in E-C translation can be got.展开更多
Neural Machine Translation(NMT)based system is an important technology for translation applications.However,there is plenty of rooms for the improvement of NMT.In the process of NMT,traditional word vector cannot dist...Neural Machine Translation(NMT)based system is an important technology for translation applications.However,there is plenty of rooms for the improvement of NMT.In the process of NMT,traditional word vector cannot distinguish the same words under different parts of speech(POS).Aiming to alleviate this problem,this paper proposed a new word vector training method based on POS feature.It can efficiently improve the quality of translation by adding POS feature to the training process of word vectors.In the experiments,we conducted extensive experiments to evaluate our methods.The experimental result shows that the proposed method is beneficial to improve the quality of translation from English into Chinese.展开更多
文摘Conversion refers to the transformation of parts of speech in some words while maintaining the original content unchanged in order to make the translated text sound smooth and fluent as well as more idiomatic in the target language. In E-C translation, conversion of pars of speech is one of the most important translation methods. Several different forms about conversion of parts of speech are introduced through analyzing the differences and usages between the two languages so that a better version in E-C translation can be got.
基金This work is supported by the National Natural Science Foundation of China(61872231,61701297).
文摘Neural Machine Translation(NMT)based system is an important technology for translation applications.However,there is plenty of rooms for the improvement of NMT.In the process of NMT,traditional word vector cannot distinguish the same words under different parts of speech(POS).Aiming to alleviate this problem,this paper proposed a new word vector training method based on POS feature.It can efficiently improve the quality of translation by adding POS feature to the training process of word vectors.In the experiments,we conducted extensive experiments to evaluate our methods.The experimental result shows that the proposed method is beneficial to improve the quality of translation from English into Chinese.
