Could Resumes Translation Be Improved With Linguistic Rules?
Gabriele Kahlout
International Journal of Computational Linguistics Research, Vol. 6, No. 4, 2015.
DOI: 
Link: 
Abstract:
When applying for jobs abroad, job seekers must translate their resumes. Google Translate can automatically
translate any text, but could its translation of resumes be significantly improved by simplifying the sentences in the input
resume?
Observing that job seekers use incomplete sentences (e.g. bullet points) to "cram in" their resumes with achievements and
industry-specific keywords, this paper describes an attempt to improve on Google's translation of resumes by re-structuring
and simplifying sentences in input resume.
Unlike initially hoped however, the proposed modifications barely improved the translations. The conclusions of this case
study may be used as further evidence in favor of "Statistical Machine Translation" over "Rule-based Machine Translation"
even when translating resumes, or as a preliminary work for further investigating the challenges of resumes automatic
translation.