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雅思写作大作文考官范文:机器翻译与人工翻译

2017.08.09 15:58

  新东方在线雅思频道特为大家收集整理了雅思写作大作文考官范文:机器翻译与人工翻译。认真研读一定的雅思范文及作文模板可以帮助我们检验自己的写作水平,并能很好地吸收和应用优秀范文里的优秀内容~更多雅思报名官网的最新消息,最新、最专业的雅思备考资料,新东方在线雅思网将第一时间为大家发布。

  >>>更多请点击:雅思写作Task 2大作文考官满分范文

  Write about the following topic:

  Machine translation (MT) is slower and less accurate than human translation and there is no immediate or predictable likelihood of machines taking over this role from humans.

  Do you agree or disagree?

  Model Answer:

  It is true that there have been great advances in technology over the last forty years. For example / For instance the use of mobile phones and e-mail communication are common these days. However, machines that translate from one language to another are still in their early stages.

  It seems to me that a machine could never do as good a job as a human, especially when it comes to interpreting what people are saying. Of course, machines can translate statements such as “Where is the bank?” but even simple statements are not always straightforward because the meaning depends on more than just words. For instance / For example the word “bank” has a number of different meanings in English. How does a translating machine know which meaning to take?

  In order to understand what people are saying, you need to take into account the relationship between the speakers and their situation. A machine cannot tell the difference between the English expression “Look out!” meaning “Be careful!” and “Look out!” meaning “Put your head out of the window”. You need a human being to interpret the situation.

  Similarly with written language, it is difficult for a machine to know how to translate accurately because we rarely translate every word. On the contrary, we try to take into consideration how the idea would be expressed in the other language. This is hard to do because every language has its own way of doing and saying things.

  For these reasons I feel that it is most unlikely that machines will take the place of humans in the field of translating and interpreting. If machines ever learn to think, perhaps then they will be in a position to take on this role.


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