Automatic translation, also for these purposes referred to as machine translation, is a component of Computational Linguistics and represents the intersection of Translation and Information Technology to explore the functions of the software that can translate text from one language to another in a legible manner.
Alan Melby, PhD in Computational Linguistics and professor at Brigham Young University, has argued that machine translation can be very useful for some technical documents that deal predominantly with very specific issues and that are drafted in a direct and repetitive writing style.
Clear examples of this can be found online with various courses from prestigious institutions of higher education in industrialized countries, namely, the Massachusetts Institute of Technology, Johns Hopkins University’s Bloomberg School of Public Health, Utah State University, the Tufts University School of Dental Medicine and ParisTech in France.
Machine translation today allows individuals and companies to customize the work by field (e.g., weather reports), which significantly improves the quality of machine translation by reducing the number of possible options for each word to be translated.
Machine translation is highly effective in areas where formal language is used or phrases are repeated without much variation. Consequently, the machine translation of administrative documents, for example, is of better quality than the machine translation of documents with a more colloquial or informal language.