| In recent years,remarkable progress has been made in the field of machine translation,which now has been widely used in the language industry.Compared with human translation,machine translation shows advantages in translation speed and availability.Despite this,machine translation quality has always been a concern.Machine translation post-editing,therefore,has become a preferred mode for many translators to guarantee quality and speed.This thesis intends to identify common errors in the machine translation of popular science texts,and to explore related post-editing strategies.This case-driven thesis is based on the translation of 2018 State of the World’s Birds,a report issued by BirdLife International to show the survival crisis facing birds.Abundant proper nouns and complex sentences scatter around the seemingly plain report,which brings challenges to the translator.After translating the report by himself,the author selected five machine translation engines to get machine outputs and classify errors based on them.Then,post-editing was conducted on the output of Google Translation,which is one of the most commonly used machine translation engines.Detailed case analysis will be given in this thesis.It is found that frequent proper nouns and references make lexical errors the most frequent category in the machine translation of a popular science text.Also,mistranslation,under translation and redundancy are frequent in machine translation.It is recommended that post-editors pay special attention to the translation of nouns and coherence between sentences or paragraphs when post-editing the translation of popular science texts. |
