• human effort in processed texts
• Machine Translation

The present work is aimed to prove the effective effort of human translators on processed texts. The work briefly introduces the history of translation and the approches and theories that have guided the subject throughout the last decades until the advent of Machine Learning and Machine Translation. The pivot point of translation is put in the forefront by focusing on CAT Tools, analyzing their properties and abilities and their current use, emphasizing their advantages and disadvantages. A first section is entirely dedicated to CAT Tools, to their evolution, to the current challenges they face and the effective advantages like time efficiency, and consistency. To broaden the perspectives of the approach to Machine Translation, thirty resources have been involved in an institutional questionnaire. The aim of the questionnaire is to investigate the approach translators have towards MT, their effective use of CAT, the reliability of the machine, and how much they are influenced by them. The project resources are then introduced. The resources involved are not only CAT Tools but even the texts subject to translation and finally the human resources. The texts involved belong to the category of technical texts covering various topics, from medicine to psychology, and from history to sustainability. The variety of texts involved is aimed to verify the abilities of the machine in different fields, whether it is capable or not to adapt the terminology to different subjects. The category of technical texts is introduced making reference to the approches and rules that govern that field of translation. The work will then be totally focused on the analysis of texts. Ten texts in Italian and ten texts in English have been processed by two different MT, ChatGPT and DeepL. The outputs are fourty in total. Two professional translators have then been involved: a mother-tongue Italian translator and a mother-tongue English one. They have been in charge of checking and verifying the outputs of the machine. The translators have worked on word files with the function of Track-Changes on to underline the amendments made. As the translators have performed the review of the texts, a linguistic analysis has been performed. The work is aimed to analyze linguistically the effort of human translators on processed texts, taking into account the amendments performed at syntactical, lexical and semantic level. On the other hand the performance of translators has emphasized the abilities of the tools highlighting even the flexibility and malleability to different areas of applications. The analysis is focused on all fourty texts to prove the effectiveness of the terminology employed throughout the different subjects involved. Finally, an evaluation of the tools is done, analyzing which tool has better perfomed the translations and what have been the main difficulties. The work of the translator has incredibly changed in recent years, the task of translation seems to have shifted to a review one, where the first is performed by the machine and the second by a human being in charge of levelling possible mistakes or misunderstandings performed by the machine. The work won't provide an aswer to what the future of translation will be but it surely will give further demonstrations to the changes we are all dealing with.